Ordered statistics-based decoding (OSD) is a soft decision decoding algorithm for linear block codes, yielding near maximum likelihood decoding performance. The OSD algorithm first sorts the received symbols in descending order based on the reliability and partitions the sorted symbols into the most reliable bases (MRB) and least reliable bases (LRB). Owing to the nature of the ordering symbols in the LRB, we presume that the expected number of errors in the leftmost (or most significant) part of LRB is relatively small compared to that in the other parts of LRB. Based on this observation, we can omit the impossible candidates in advance, by using Hamming weights of partial syndromes. This results in huge computational savings without compromising the decoding performance. Compared with OSD based on probabilistic necessary conditions and probabilistic sufficient conditions [3], [4], incorporation of the proposed algorithm into fast and scalable OSD [7] exhibits speed-up gains of a factor of approximately 405 (at 3.0 dB) for (127,64) BCH codes (maximum order 5), without compromising the decoding performance.

This study presents a hash rearrangement scheme to improve coding efficiency of high‐efficiency video coding for screen content (HEVC‐SCC) by sharing hashes of the inter‐search with intra block copy (IBC). Of the various methods introduced during the HEVC‐SCC development, the IBC search technique can yield tremendous coding gains, but creates a massive computational burden on the encoder side. The authors propose an effective way to generate the IBC hash table to avoid redundant operations required for hash entry computation. Moreover, the authors propose a hash rearrangement scheme to apply the second hashes used in the inter‐search to IBC and the corresponding IBC search method to reduce the computational burden and to improve the coding efficiency. The experimental results show that compared with the HEVC‐SCC test model (SCM)‐8.0, the proposed algorithm results 80% time reduction when considering IBC hash generation itself, and can save 9–30% of hash generation time even taking into account the proposed second hash generation. It can also reduce the hash‐based IBC search time by 14.61%. Furthermore, the proposed algorithm can achieve Bjontegaard delta bit rate savings of −0.66, −0.45 and −0.66% on average for all intra, low‐delay, and random access coding structures, respectively.

In this paper, we propose a four-direction residual interpolation (FDRI) method for color filter array interpolation. The proposed algorithm exploits a guided filtering process to generate the tentative image. The residual image is generated by exploiting the tentative and original images. We use an FDRI algorithm to more accurately estimate the missing pixel values; the estimated image is adaptively combined with a joint inverse gradient weight. Based on the experimental results, the proposed method provides a superior performance in terms of objective and subjective quality compared with the conventional state-of-the-art demosaicking methods.

This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaicking algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

The constrained one-bit transform (C1BT) was proposed to increase the motion estimation (ME) accuracy of the previous one-bit transform (1BT) especially for small motion blocks. Although making another bit-plane is very simple and efficient, its performance is even better than that of the two-bit transform (2BT) based ME. However, unlike the 1BT-based ME and the 2BT-based ME, the successive elimination algorithm (SEA) based on the triangle inequality for C1BT-based ME cannot be derived because C1BT matching error criterion does not satisfy the typical measure conditions. In this letter, a fast full-search block matching algorithm for C1BT-based ME is developed. The proposed algorithm evaluates lower bounds for constrained one-bit matching criterion based on the Bonferroni inequality to eliminate the impossible candidates faster and save computations substantially. Experimental results show that while the ME accuracy of the proposed algorithm is the same as that of the full search C1BT, the proposed algorithm reduces computational complexity significantly.

In this paper, we present a novel color image demosaicking algorithm using a voting-based edge direction detection method and a directional weighted interpolation method. By introducing the voting strategy, the interpolation direction of the center missing color component can be determined accurately. Along the determined interpolation direction, the center missing color component is interpolated using the gradient weighted interpolation method by exploring the intra-channel gradient correlation of the neighboring pixels. As compared with the latest demosaicking algorithms, experiments show that the proposed algorithm provides superior performance in terms of both objective and subjective image qualities.

This paper presents a weighted least squares-based intrafield de-interlacing algorithm. First, we formulate the estimation of the missing pixels as a maximum a posteriori (MAP) framework. We deduce the weighted least squares structure from MAP based on the analysis of the statistic model of the original high-resolution images and the associated statistical model of the given low-resolution images and original high-resolution images. The weights affect the estimation of the statistical model. We also design adaptive weights to match regions with different properties. The method is compared with other de-interlacing algorithms in terms of PSNR and SSIM objective quality measures and de-interlacing speed. It was found to provide excellent performance and the best quality-speed tradeoff among the methods studied.

This paper introduces an efficient intra-field deinterlacing algorithm that is based on Taylor series expansion and polynomial regression. In order to estimate the value of an interpolated point using the given data, we rely on a generic local approximation function around this point for estimating the missing data. The well knownN-term Taylor series expansion is regarded as a local representation of the approximation function, and we use polynomial regression to find the optimal local approximation of the function. Instead of estimating the edge orientations as in previous intra-field deinterlacing methods, such as an edge-based line average, we propose an efficient deinterlacing method, which does not consider directional difference measurements that use limited candidate directions. When compared with existing deinterlacing algorithms, the proposed algorithm improves the peak signal-to-noise-ratio while maintaining a high efficiency.

In this paper, we introduce an efficient intra-field deinterlacing algorithm based on moving least squares (MLS). The MLS algorithm has proven successful for approximating scattered data by minimizing a weighted mean-square error norm. In order to estimate the value of the missing point using the given data, we utilize MLS to generate a generic local approximation function about this point. In the MLS method, we adopt trigonometric functions to approximate the local function. This method is compared to other benchmark algorithms in terms of peak signal-to-noise ratio and structural similarity objective quality measures and deinterlacing speed. It was found to provide excellent performance and the best quality-speed tradeoff among the methods studied.

Recently automatic video surveillance in the digital video recording CCTV system is rapidly becoming one of the most accepted security system. The dangerous situations such as forest fire, flood, and terrorism are increasing, and cause serious casualty and property loss. In this paper, we particularly focus on the fire detection system in video. The proposed block-based fire detection algorithm consists of three basic steps. In the first step, we find motion vector utilizing optical flow and distinguish the suspect as fire region. In the second step, we conduct chromatic detection based on Lab color space. In the final step, we employ motion information for detecting the correct fire block by using the characteristics that fire goes almost upward. Experimental results show that the proposed method yields good performance for fire detection.

This paper proposes an efficient intra-field deinterlacing algorithms using local adaptive rational interpolation filter (LARF). Experimental results show that the proposed algorithm provides satisfied performances in terms of both objective and subjective image qualities. What is more, it just exploits the local spatial gradient information among the neighboring pixels without complex preset-conditions which has lower complexity than most of the existing algorithms.

To reduce temporal redundancy, conventional video coding standards, such as H.264/AVC, use block based motion estimation (ME) and compensation algorithm. However, the coding performance of H.264/AVC significantly drops when characteristics of video contents are changed due to the motion. In this paper, we proposed a pre-filtering algorithm with locally adaptive filter set for the reference frame to minimize the prediction error in the ME process. With image statistics, we adaptively construct a pre-filter set and apply the pre-filter set to the reference frame locally. The proposed algorithm is more efficient in sequences that have high resolution or fast motion. By manipulating the reference frame similar to the current frame, the coding performance is significantly improved. Compared with H.264/AVC, the proposed algorithm achieves bit-rate reduction up to 15.28%.

In this paper, adaptive fast matching algorithms are proposed based on the sub-block ordering. Proposed two algorithms for the lossless fast matching only reduce the unnecessary matching complexity of motion estimation in the video coding. By observing the expectation of the sum of absolute differences between the current sub-block and a reference sub-block in the pixel domain, we derive an absolute difference model which indicates the relationship between the sub-block distortion and the intra sub-block complexity. In the same way, we consider the inter complexity among all sub-block with the absolute difference model. From the absolute difference model, we derive the transform coefficient model for measuring the sub-block complexity in the transform domain based on the Parseval's theorem. Experimental results show the proposed fast matching algorithms reduce the unnecessary complexity of the full search algorithm about 20% on average without any loss of image quality.

This paper introduces an adaptive postprocessing method in block-based discrete cosine transform (BDCT) coded images. We present a framework, which is a serial-concatenation of a 1-D simple deblocking filter and a 2-D directional filter. First, we classify the simple deblocking filter by an adaptive threshold depending on local statistical properties, and update block types appropriately by a simple rule, which affects the performance of deblocking progresses. Second, a 2-D directional filter is introduced to suppress the ringing artifacts caused at the sharp edges and the block discontinuities while preserving true edges and textural information. Finally, comprehensive experiments indicate that the proposed algorithm outperforms lots of deblocking methods in the literature, in terms of evaluation of PSNR and subjective visual qualities.

H.264/AVC is adopted to a variety of applications because of its high compression efficiency. The high coding efficiency of H.264 is mainly acquired from the newly allowed prediction schemes including variable block mode. However these schemes require a high complexity to select the optimal mode. In this paper, to reduce this large computational burden, an adaptive fast inter mode decision algorithm using dynamic threshold technique for H.264/AVC P slices is proposed. In many sequences, the modes for large block such as SKIP and P16times16 occupy the most portions optimal modes. This fact gives us very important clue. The experimental results show that the proposed mode decision algorithm can reduce entire encoding time effectively by about 42.5% only without noticeable PSNR loss.

This paper investigates a new interpolation technique based on content adaptive interpolation with fuzzy reasoning. The proposed technique reduces image artifacts in regions where moving object cannot be well traced by motion estimation. Our proposed method consists of two parts: content classification and fuzzy weight assignment process. The spatial deinterlacing methods have been studied excessively in literature. The edge based line average method yields relatively good performance with low complexity. On the basis of the above method, six useful measurements are obtained within the 5-by-3 spatial window to prevent false edge direction decisions in computing the direction where the interpolation is to be operated. The simulation results indicate that the developed method can generate high quality intra-interpolation picture for interlaced images.

This paper considers the LDPC-based Slepian-Wolf coding with decoder side information. The paper analyzes the statistical properties of LDPC syndromes and shows that there are residual redundancies in LDPC syndromes, especially at low rates. Furthermore, this paper proposes a rate-adaptive way to compress LDPC syndromes.

Most of previous interpolation methods cannot consider the sufficient edge information, and that result in unwanted artifacts. To remove or reduce the problem effectively, we propose a new image interpolation scheme based on Weighted Edge Pattern Analysis (WEPA). Proposed algorithm finds the accurate edge direction at current pixel by using the Spatial Direction Vector (SDV) which is result of WEPA of the neighboring pixels. After direction refinement, we interpolate the current pixel along obtained final SDV direction. Experimental results show that the proposed method exhibits a better performance than previous methods in both objective and subjective results with a variety of still images.

Most commercial digital still cameras use a single sensor array (e.g., CMOS or CCD) with color filter array (CFA) to reduce the cost and size. Since the image obtained with CFA has only one color value per pixel, the demosaicing is needed to acquire missing two color values. Although many demosaicing methods have been proposed, they still have artifacts such as rainbow and zippering artifact. In this paper, we propose the simple demosaicing algorithm using tendency of neighbor pixels with the enhanced weighting function. In the experimental results, our algorithm shows much better subjective qualities of the images than conventional demosaicing algorithm and improves objective qualities.

In order to achieve a high coding gain, the H.264 video coding standard allows one or more reference frames. However, this greatly increases the computational burden in proportion to the number of the searched reference frames. Therefore, we propose a method to reduce the complexity by selecting the proper reference frames. The proposed algorithm uses the optimal reference frame information in both the P16 times 16 mode and the adjacent blocks, thus decreasing any unnecessary searching process in the inter modes except for P16 times 16. Experimental results show that the proposed method considerably saves coding time with negligible quality and bit-rate difference. It can also be adopted with any of the existing motion estimation algorithms to obtain additional performance improvement.

This paper proposes an improved algorithm of the error-resilient entropy coding (EREC). The idea is to record and transmit the states of variable-length data blocks (VLBs) and fixed-length data slots (FLSs) during EREC encoding process. The state information (SI) of VLBs and FLSs is used at the receiver to resynchronize VLBs during EREC decoding process. It is proved that the cost of SI is fewer than 3 bits per VLB. To combat errors in SI bits, we propose to code SI bits into EREC structure. Experimental results show that our proposed method improves recovery quality of VLC bitstream significantly.

Video deinterlacing can be realized using time-space interpolation filters. To improve video deinterlacing quality with respect to missing pixels on moving diagonal lines, we developed a fuzzy concept that utilizes deinterlacing methods. The proposed algorithm consists of three parts. The first part is fuzzy rule-assisted edge-preserving-based deinterlacing (FED), which has an edge-preserving unit that utilizes fuzzy theory to find the most accurate edge direction and interpolates the missing pixels. Using the introduced gradients in the interpolation, the vertical resolution in the deinterlaced image is subjectively concealed. The second part is weighted fuzzy-reasoning-assisted deinterlacing (WFD), which works in the spatio-temporal domain. In this part, the computed weights are considered and multiplied by the candidate deinterlaced pixels, which successively build approximations of the deinterlaced sequence. The third part of the proposed algorithm is weighted fuzzy switching filtering, which analyzes the suitability of each method on system performance and uses a switching algorithm between FED and WFD. The outcome of image interpolation can be adjusted continuously by varying the setting of the membership function for fuzzy inference. Compared with conventional image interpolation methods, the algorithm presented in this paper provides improved edge quality in the deinterlaced image without the introduction of evident artifacts.

This paper addresses the problem of edge restoration in digital images. Taking advantage of an ensemble approach, multiple type-1 fuzzy filters are combined to reach a decision. The fuzzy logic concept for linguistic variables and possibility theory is discussed with regard to knowledge representation and inference procedures. To improve conventional deinterlacing issues, we adopt type-1 fuzzy set concepts to design a weight-measuring approach. We demonstrate that the fuzzy ensemble approach model is well suited to image processing and provide case studies in the video-deinterlacing field. In our proposed method, five fuzzy membership functions (MFs) of linguistic variable-based fuzzy logic filters are derived from the type-1 (a.k.a. ordinary or primary) fuzzy MF. The weight-measuring process of our proposed model is used to assign weights to six candidate deinterlaced pixels (CDPs) that are interpolated according to edge direction. The use of a different MF for each direction allows the filter to characterize each pixel variation influence independently, according to its direction. The weights from all MFs are multiplied with the CDPs. The results of the empirical trials clearly show that the proposed system can successfully deal with several image types containing motion or detail elements.

We intuitively derive DC and AC constraints to model local block complexities using ordered Hadamard transform from pixel based gradient method. For lossless motion estimation (ME), using (1), we obtain the optimized search order in the matching error calculation by descending order of local constraints using sum of these two constraints. LBC(k) = ACSum(k) + |DCMB- DCLB(k)|.

In this paper, we propose a new weighted fuzzy filter, which selectively uses spatial and temporal information. The accuracy of the edge direction detection, motion detection, and interpolation is crucial key factors to obtain excellent visual quality in deinterlaced images. The adopted fuzzy concepts are utilized to design a weight-evaluating technique. The weights were considered to be multiplied by the candidate deinterlaced pixels. Experimental results demonstrate that the proposed deinterlacing method performs better than previous techniques.

In this paper, we propose a new interpolation algorithm based on edge-weighted method, which improves the bilinear interpolation method. The conventional bilinear interpolation has a serious problem which is the blurring artifact crumbling the edge components. In this paper, the edge-weighted image (EWI) interpolation algorithm, which enhances the edge components, is proposed. In the experimental results, not only did the EWI interpolation exhibit much better subjective qualities of the images than conventional bilinear interpolation, but also improved objective qualities.

In this paper, we describe a new spatial domain deinterlacing algorithm which based on the fuzzy weight function. This technique is applied to the issue of missing pixel calculation in video deinterlacing. Traditional edge-based deinterlacing methods became poor at detecting precise edge direction which influences deinterlacing performance. Also, they do not use all edge direction information together but just use only one edge direction. In the proposed algorithm, weights are extracted from luminance difference values and multiplied by the candidate deinterlaced pixels. The extracted weights are worth to be used for proposed method to calculate the edge direction precisely. Compared to the conventional edge-based deinterlacing method, the proposed algorithm provides good visual results in various kinds of edges.

H.264/scalable video coding (SVC) is a new compression technique that can adapt to various network environments and applications. However, despite its outstanding performance, H.264/SVC has considerable complexity burden on decoding, especially in inverse transform and interpolation for motion compensation. We first analyze the Joint Scalable Video Model (JSVM) decoder to identify time-consuming modules of H.264/SVC. Based on the analysis, we present the single instruction multiple data (SIMD) Optimization methods for 4×4 inverse transform and interpolation for motion compensation with an efficient data structure. On a 2.4 GHz Intel Pentium IV processor, the proposed methods reduce considerably the computation time for inverse transform and interpolation for motion compensation, compared to JSVM software.

In this paper, an efficient algorithm for the fast full search is proposed to reduce the computational cost of block matching algorithm for motion estimation in video coding. Based on the characteristic of the pixel histogram for the current macroblock, the proposed fast matching method adaptively sorts the matching order pixel-by-pixel for each macroblock. Also, partial distortion elimination (PDE) method was used to terminate the improper candidate macroblocks early after the process of multilevel successive elimination algorithm (MSEA). The varieties of test sequences were simulated and the experimental results demonstrate that the proposed algorithm achieves less computational load.

Wyner-Ziv (WZ) video coding, or lossy coding of video with decoder side information (SI), is a new video coding paradigm which provides the potential of shifting encoder complexity to decoder. Due to the fact that correlation among adjacent frames varies spatially and temporally in a video sequence, in WZ video coding, the quality of SI generated at the decoder also varies accordingly. This implies that more parity bits should be sent for locations where the quality of the SI is poor, while fewer parity bits for locations where the quality of the SI is good. For this reason, this paper proposes a WZ video coding scheme with block classification. In the scheme, according to difference between blocks in a WZ frame and its adjacent key frame, the blocks in a WZ frame are classified into classes of different importance. A strategy is designed so that the more important a class is, the more bits will be transmitted for it, and this leads to savings in bit rate. Simulation on various test video sequences shows that, compared to a similar scheme without block classification, the proposed scheme can achieve a bit rate savings of up to 42.44% with only slight PSNR loss in some cases.

Resynchronization makers (RM) are widely used in variable-length coding (VLC) bit stream to limit error propagation. However, the insertion of RMs introduces some decrease in coding efficiency unavoidably. To make a compromise between coding efficiency and error-resilience, this poster proposes a novel approach to the optimal RM positioning in which the valid-length ratio (VLR) is used as the measure of information. Hence, the optimization problem is converted into maximizing the VLR under a certain channel conditions

We considered the problem of resampling video frames to adjust from 176x72 to 352times288 display formats. Images were divided into six regions according to six different edge directions and different reconstruction techniques were employed in each region. The algorithms developed and implemented on this system include edge pattern-based region classifier and resampling strategies for digital display. The performance of the proposed algorithm is compared to conventional methods such as nearest-neighbor interpolation, bilinear interpolation, and simple cubic curve fitting interpolation.

A deinterlacing algorithm that is based on rough set theory is researched and applied. In this paper, rough sets serve as a tool for data analysis and knowledge discovery from test sequences. The proposed deinterlacing approach employs a size reduction of the database system, keeping only the essential information for the process. This approach automatically selects the best deinterlacing approach. Decision making and interpolation results are presented.

In this paper, we propose a Wyner-Ziv video coding scheme with spatio-temporal side information. In the scheme, temporal side information is generated through motion compensated temporal interpolation, using frames that are already decoded. While spatial side information is created through spatial prediction, using the temporal side information. The spatio-temporal side information are both incorporated into a turbo code based Slepian-Wolf decoder to decode the quantized source, but only temporal side information is used for reconstruction. Extensive simulations over various test video sequences show, compared with a similar codec with only temporal side information, the proposed scheme can achieve more than 20% bit rate savings without sacrifice in PSNR, and hence significantly improves the coding efficiency.

This paper presents a novel intra deinterlacing algorithm (NID) based on content adaptive interpolation. The NID consists of three steps: pre-processing, content classification, and content adaptive interpolation. There are also three main interpolation methods in our proposed NID, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the NID method performs better than previous techniques.

This paper proposes a novel fuzzy reasoning interpolation method for video deinterlacing. We propose SMDW and TMDW parameters to measure the amount of entropy in the spatial and temporal domains. The shape of the membership function is designed adaptively according to the parameters, and can be utilized to determine edge direction. Our proposed fuzzy edge direction detector follows three processing steps: fuzzification, rule inference, and defuzzification. This filter operates by identifying small pixel variations in nine orientations (0°, ±30°, ±45°, ±55°, and ±60°) in each domain, and works by using rules to infer the edge direction. Detection and interpolation results are presented. The results of computer simulations show that the proposed method is able to outperform a number of methods in the literature.

DWT has been the basis of image compression, such as in JPEG2000. This paper proposes a novel VLSI architecture that performs line-based DWT using a lifting scheme. The architecture consists of row processors, column processors, an intermediate buffer and a control module. The intermediate buffer is composed of FIFOs to store temporary results of horizontal filters. The control module schedules the output of wavelet coefficients to external memory with the priority from high to low. Horizontal filtering and vertical filtering are simultaneous, and all levels of DWT are processed parallel. The presented architecture finishes multi levels of 9/7 DWT in one image transmission time. Meanwhile, it decreases significantly memory used and hardware resource required. This architecture is suitable for various real-time image/video applications.

For the improvement of coding efficiency, the H. 264 standard uses new coding tools. Among the tools, motion estimation using smaller block sizes leads to higher correlation between the motion vectors of neighboring blocks. This characteristic of H.264 is useful for motion vector recovery to conceal a lost macroblock. In this paper, we propose the motion vector recovery method based on optical flow in H.264. We first determine optical flow region to alleviate the complexity, and choose initial value of flow velocity using neighboring motion vectors of a lost macroblock. And then the proposed method recovers the motion vectors of 4×4 blocks included in a lost macroblock using the weighted average of obtained flow velocities. Simulation results show that our proposed method gives higher objective and subjective visual qualities than conventional approaches.

For improvement of coding efficiency, the H.264 video coding standard uses new coding tools, such as variable block size, quarter-pixel-accuracy motion estimation, multiple reference frames, intra prediction, loop filter, etc. Using these coding tools, H.264 achieves significant improvement in coding efficiency compared with existing standards. However, encoder complexity increases tremendously. Among the tools, the macroblock mode selection and the motion estimation contribute most to total encoder complexity. This paper focuses on complexity reduction in macroblock mode selection. Of all macroblock modes which can be selected, inter8×8 and intra4×4 have the highest complexity. We propose two methods for complexity reduction of inter8×8 and intra4×4 by using the costs of the other macroblock modes. Simulation results show that the proposed methods save up to 57.7% of total encoding time compared with the H.264 reference implementation, whereas the average PSNR only decreases less than 0.05dB.

A new method combining source channel coding with source modeling and network congestion control for reliable video transmission over wireless network is proposed in this paper. Based on scene modeling and characteristic analyzing, all layers generated by scalable coding are classified into several types and two queuing are made respectively according to their contribution to network congestion and to the quality of reconstructed video. Then the source rate, protection level and congestion control strategy are dynamically adjusted according to different error status in which the packet loss is caused by network congestion or by unreliable transmission in wireless channel. The simulation results show that our proposed approach can achieve better results than MPEG-4 video source coding with fix rate Turbo coding and than the one which dynamically adjusting source coding and channel coding rates only.

H.264 adopts new coding tools such as variable block size, quarter-pixel-accuracy motion estimation/compensation, multiple reference frames, loop filter, etc. The adoption of these tools enables a macroblock to have more information compared with previous standards. In H.264 each macroblock can have up to sixteen motion vectors, four reference frames, and a mode of the macroblock, all of which can be used for temporal error concealment. The H.264 error concealment in the informative part, however, uses a similar method to prior coding standards that consider only motion vectors of macroblocks adjacent to the lost macroblock. In this paper, we propose an effective temporal error concealment algorithm for H.264-coded video. It uses not only motion vectors and reference frames but the modes of macroblocks adjacent to the lost macroblock as well. Depending on the modes of neighboring macroblocks, each lost macroblock is concealed on the basis of different block sizes. Simulation results show the proposed method yields better video quality than conventional approaches.

In video transcoding, the compressed video bit stream is often converted to the reduced frame rate video bit stream in order to reduce the bit rate. To speed up this operation, a video transcoder usually reuses the decoded motion vectors from the incoming bit stream. Previously, the bilinear interpolation method and forward dominant vector selection method were proposed to compose the missing motion vectors for reuse. In this paper, we propose a new algorithm, called the efficient-forward dominant vector selection, which utilizes the difference between dominant macroblock and motion vector from the incoming ones. We propose a motion vector refinement algorithm called the direction oriented search. The performance of experimental results can be improved while maintaining low computational complexity for a reduced frame rate video transcoder.

The adaptive and powerful coding schemes in H.264 provide significant coding efficiency and some additional merits like error resilience and network friendliness. In spite of these outstanding features, it is not easy to implement H.264 codec as a real-time system due to its high requirement of memory bandwidth and intensive computation. Although the variable block size motion compensation using multiple reference frames is one of the key coding tools to bring about its main performance gain, it demands substantial computational complexity due to exhaustive search among all possible combinations of coding modes. Many existent fast motion estimation algorithms are not suitable for H.264 having variable motion block sizes. In this paper, we propose the motion field adaptive search using the hierarchical block structure based on the diamond search applicable to variable motion block sizes.

We propose a lossless compression algorithm for bi-level images based on context selection and hierarchical enumerative coding. To exploit inter-pixel correlation in an image, a context that is calculated from coded pixels is obtained to rearrange a 2-D image to a 1-D binary string, and the resulting 1-D sequence undergoes hierarchical enumerative coding. The proposed method attains performance similar or superior to existing state-of-the-art schemes. Also, since the required operations are only addition and comparison, its computational complexity is substantially low.

We propose a novel compression algorithm for cell animation images. Conventional software algorithms include Cinepak, MPEG-1, Indeo5, etc., but these are for natural images, not for cell animation images. At low bit-rates, these provide relatively very poor image quality. In the proposed method, for intra frame coding, octree-based color quantization, ADPCM, and Golomb-Rice code are used. And for inter frame coding, block-to-block difference information is classified and coded. Therefore computational complexity is relatively low. The proposed methods outperform MPEG-1, FLC, and Indeo 5.

In the context of image coding, a number of reversible integer-to-integer wavelet transforms were previously proposed and compared with respect to their lossy compression performance, lossless compression performance, and computational complexity. Among the transforms, some of them were found to perform particularly well. In this paper, we propose a unified framework for several efficient transforms using the lifting scheme. We represent the transforms with simple parameters. The parameters are usually dependent on the input signal. We give mathematical formulations on the framework and experimental results as well.

This paper proposes a novel blocking artifacts reduction method based on the notion that the blocking artifacts are caused by heavy accuracy loss of transform coefficients in the quantization process. We define the block boundary discontinuity measure as the sum of the squared differences of pixel values along the block boundary. The proposed method compensates for selected transform coefficients so that the resultant image has a minimum block boundary discontinuity. The proposed method does not require a particular transform domain where the compensation should take place; therefore, an appropriate transform domain can be selected at the user's discretion. In the experiments, the scheme is applied to DCT-based compressed images to show its performance.

We propose a novel blocking artifacts reduction method in image coding based on the least square block discontinuity criterion. We define the "inner product on the block boundaries" for N/spl times/N 2-D functions to introduce the concept of the "boundary-orthogonal 2-D functions". The proposed post-processing approach attempts to find the coefficients of the boundary-orthogonal 2-D functions whose pel-by-pel sum is added to the blocky image to minimize the block discontinuity. Experimental results, using DCT-based compressed images, are provided to show the performance of the proposed scheme. In the experiments, as a special case of the proposed method, we use three terms of 2-D DCT functions which turn out to be simple but very effective in reducing blocking artifacts.

This paper proposes a simple and efficient realization of letter-box conversion for displaying 16:9 images on a 4:3 screen. Compared to the true 16:9 letter-box display where 4:3 vertical decimation is used, the new method yields 5:3 display aspect ratio (slightly wider than 16:9 in the vertical direction) by using 5:4 vertical decimation, and enables the decimation filter to be implemented exactly and easily without multipliers. An efficient hardware architecture is also shown for implementing the proposed 5:4 decimation; in case of progressive scan, if requires only two m-bit adders and two m-bit 2:1 multiplexers where m is the number of bits (typically 8) per pixel. Experiment shows little visual difference between the proposed letter-box conversion and the true 16:9 display with the 4:3 decimation.>

A definition of generalized discrete-time time-frequency distributions is introduced. This definition utilizes the full information provided by a data sequence so that one can avoid aliasing which is troublesome in the existing definition. The formulation provides a unified framework for implementing Cohen's class of generalized time-frequency distributions which was formulated in the continuous-time domain. Some requirements for the discrete-time kernel in the approach are discussed in association with desirable distribution properties.>

A novel fast recursive O(N) algorithm for bit-reversal permutation of a data array is presented. Exploiting regularity in the bit-reversal and eliminating redundant computations, this new method provides a considerable improvement in computational time. This computational efficiency results from the fact that every permutation index is basically computed by a single logical or arithmetic operation between a previous index and a proper offset. Experiments show that it is faster than any other bit-reversal algorithms that seem to be available. The performance of this method is compared to that of other bit-reversal method. Extension of the method to general digit reversal is described. Bit-reversal permutation of two-dimensional arrays is also discussed.>