This paper presents a method for evaluating the quality of images altered by Gaussian blur. The method is based on the observation of bokeh mode images where the region of interest (foreground) is sharp, while the remaining parts (background) are intentionally blurred to enhance the perceptual quality of the image. The blurriness of the background increases attention towards the foreground part of the image. The proposed quality metric is obtained by combining the attention factor and the sharpness of the region of interest. The accuracy, in terms of Spearman’s-rank-order correlation-coefficient (SROCC), for popular and publicly available databases such as LIVE, VCL, TID2008, CSIQ, and TID2013, is 0.963, 0.925, 0.900, 0.930, and 0.930, respectively. The proposed method achieves high and consistent Spearman’s rank-order correlation coefficient (SROCC) values compared to the majority of state-of-the-art algorithms. Furthermore, in terms of speed, the proposed method surpasses other state-of-the-art methods. The MATLAB code of the proposed metric is publicly available at https://drive.google.com/drive/folders/1SRmUp0N157Ati9l3kV13uoCxw5PhMgQn?usp=sharing .

The wavelet block tree coding (WBTC) algorithm is an efficient wavelet‐based image coder. In this coder, multiple spatial orientation trees are combined together to make a single block tree. It uses three ordered lists to keep track of significant/insignificant coefficients and sets while coding, which increases its memory requirement as well as computational complexity. Also, it uses memory inefficient conventional discrete wavelet transform (DWT) to compute the transformed coefficients. In this study, a Low‐Complexity Block Tree Coding (LCBTC) algorithm that uses two state‐tables and two very small lists, is proposed. Similar to WBTC, it also uses sorting and refinement passes in each bit‐plane. However, it encodes the coefficients in block‐tree manner using depth‐first search approach to reduce the computational complexity. It uses DWT coefficients obtained from modified fractional wavelet filter (MFrWF) rather than conventional DWT, which further reduces the overall memory and complexity of the image coder. The simulation results show that the memory requirement and computational complexity of LCBTC is much less than WBTC and other state‐of‐the‐art coding algorithms. These features make the image coder a better candidate for compression in memory constrained and real‐time visual sensor networks.

In this paper, a low complexity compressive sensing (CS) based scalable image codec is proposed. At the encoder side, hierarchical wavelet decomposition of an input image is used that results in one low-frequency subband with no sparsity and a number of high-frequency subbands having sparsity. An adaptive measurement process is then applied on detail subbands to select the number of measurements. Set Partitioning in Hierarchical Tree (SPIHT) is used to encode the measurements to get a scalable bitstream. At the decoder, a non-iterative pseudoinverse algorithm with low complexity for CS reconstruction is used. Results show that the proposed method gives a PSNR improvement of 1 to 3.5 dB compared to other algorithms. Moreover, being non-iterative, the proposed codec is also having extremely low complexity.

The segmented fractional wavelet filter (SFrWF) allows the use of the fractional wavelet filter (FrWF) on line segments, thus can easily be implemented on low-memory devices and sensor nodes to compute the discrete wavelet transform of images. However, the complexity of SFrWF is relatively high due to the use of overlap and add method used in it for avoiding the boundary discontinuities at the segment boundaries. The high complexity of SFrWF makes it unsuitable for low-cost visual sensors used in wireless visual sensor networks (WVSNs)/Internet of things (IoT). In this paper, a lifting-based implementation of SFrWF with 9/7 filter-bank is presented with the aim to reduce it's computational complexity. The proposed lifting based implementation requires fewer computations than SFrWF. Furthermore, the proposed implementation uses an alternative approach to avoid the border discontinuities at segment boundaries. Evaluation results show that for high-resolution ( 2048×2048) images, the complexity of proposed implementation is approximately 40% less than that of SFrWF, without any additional memory requirement.

This paper proposes a novel energy efficient architecture for computing Discrete wavelet transform (DWT) of an image using the Fractional wavelet filter (FrWF) approach. The proposed architecture needs to read only a single image line in memory at a time, which results in less memory requirement. The performance of the proposed architecture is compared with existing FrWF architecture by implementing both the architectures on same FPGA board. Experimental results demonstrate that for an image of dimension 512×512, the proposed architecture has 50% lower number of computational cycles, requires 80% less number of multipliers, and 47.34% lower energy consumption than the FrWF architecture. The lower hardware resource requirement, reduced power consumption and reduced energy consumption of the proposed architecture make it suitable for computing DWT of images over Wireless multimedia sensor networks/Internet of things.

The popular histogram equalisation (HE) technique, which was developed to improve the image contrast, sometimes may also be misused to hide intensity variations in tampered images with ill intention. The authors investigate how existing image forensic techniques may fail to detect HE operation in highly compressed and low‐resolution images. They then propose an algorithm to detect whether a given image (either uncompressed or JPEG compressed) has undergone the HE process or not. It is based on the frequency domain analysis of image histogram and exploits the difference in DC and AC coefficients in histogram's discrete Fourier transform. It can detect HE operation even if the image is saved in JPEG format after the equalisation, where most the existing algorithms fail. The extensive computer simulations over large dataset show the effectiveness of the proposed algorithm.

In the modern era of Internet, many user-end applications require the estimation of quality of images directly from the bitstreams, as the original image may not be available. This is a challenging issue. In this paper, we propose a novel approach of no-reference (NR) objective quality assessment of wavelet coded images. The proposed method is based on estimation of the contribution of each received bit in an embedded bitstream in the reduction of mean-square error (MSE), assuming initial image with all zero pixel values. Mathematical analysis is carried out to estimate the quantization errors in terms of MSE reduction, in wavelet-based SPIHT coding algorithm. The simulation results demonstrate the effectiveness of the proposed method.

The conventional network layers are mainly designed for fixed networks and are not suitable to cope the challenges offered by the modern wireless networks. Moreover, certain functionalities can be implemented simultaneously in more than one layer. For example, unequal error protection (UEP) can be performed at the application layer, using forward error correction (FEC), but it is bandwidth inefficient. On the other hand, UEP can also be performed at the physical layer using hierarchical modulation to protect higher priority bits more strongly without any additional bandwidth, but at the cost of increased errors in the lower priority bits. The authors propose a cross-layer UEP approach to enhance reliability of scalable video by combining adaptive FEC at the application layer and hierarchical quadrature amplitude modulation (HQAM) at the physical layer. The idea is to slightly reduce the FEC protection of higher priority bits and increase the FEC protection of low-priority bits in such a fashion that the overall data rate at the application layer remains unchanged. The higher priority bits are additionally protected using HQAM at the physical layer. Simulation results show significant improvements in performance when the proposed scheme is used.

In this paper, we propose a unified approach of exploiting both inter- and intra-band correlations among the wavelet coefficients in a single algorithm. Most of the existing wavelet based image coding techniques are either based on zero-tree approach or zero-block (quad-tree) approach. The zero-tree based coders exploit only inter-band correlations whereas zero-block based coders exploit only intra-band correlations among the wavelet coefficients. Thus this work is an attempt to fuse the features of both block- and tree-based coding algorithms into a single algorithm. The proposed algorithm generates fully embedded bit stream. Simulation results show that the proposed algorithm outperforms existing wavelet based image coders. Additionally, the memory requirements due to the auxiliary lists is also reduced as compared to the zero-tree based coders

In this paper, we propose a simple and efficient technique for embedded color image coding. The proposed algorithm exploits inter- and intra-subband correlations of the wavelet transformed luminance (Y) and chrominance (U and V) planes as well as the interdependency among the coefficients of the three-color planes. The coefficients of the three-color planes are linked through the composite spatial orientation trees (CSOT) having root nodes in the Y-plane only. The CSOT is defined for blocks of coefficients rather than a single coefficient. Thus, the proposed algorithm combines the features of both zero-tree and zero-block based algorithm into a single algorithm due to the use of block-tree hierarchical structure. Simulation results show the improved performance of the proposed algorithm over other sate-of-the-art coders such as MPEG-4, color SPIHT (CSPIHT), color SPECK (CPECK), and JPEG-2000.

This paper presents a memory efficient version of set partitioning in hierarchical tree (SPIHT). The proposed coder termed as memory efficient SPIHT (MESH), uses a single re-usable list instead of three continuously growing linked lists as in conventional SPIHT. The list is re-initialized at the beginning of each bit-plane (coding pass) and is exhausted within that bit-plane itself. Another feature of the proposed coder is that it uses a single pass for each bit-plane by merging the sorting and refinement passes of conventional SPIHT together. The reinitialization of the list in each bit-plane makes the proposed coder inherently error resilient. The performance of the proposed coder is measured in terms of coding efficiency and the worst case memory requirements for list entries in each bit-plane. The performance comparison with SPIHT shows that the proposed algorithm results in 50-70% memory saving while retaining a coding efficiency comparable to SPIHT.

This paper introduces techniques for segmentation and tracking based on analysis of region derived descriptors. By partitioning the image into a series of homogeneous regions, the problem of object extraction changes from pixel based to database analysis. A region based approach has distinct advantages over pixel. In particular, it has low dimensionality, is resilient to rotation, shear, and photometric changes, preserves boundaries, gives implied segmentation, provides comprehensive description, has reduced drift, and permits detailed analysis. The method is amenable to the introduction of prior knowledge permitting the simplification of segmentation, which is otherwise an ill-posed problem. Objects are defined as collections of contiguous regions with known statistics, allowing their identification by performing correlations in the database. The interframe difference of region based sequences is high for low-motion scenes due to segmentation noise, but performs consistently better for high motion, making it suitable for tracking. When applied to tracking the method proves robust, occlusion insensitive, and unlike the other techniques, it re-establishes lost lock.

The work presents an embedded and memory efficient image compression algorithm which exploits both inter- and intra-band correlation of wavelet coefficients. Set partitioning in hierarchical tree (SPIHT) is a zero-tree based coder which exploits inter-band correlation among bands of the same orientation, while the set-partitioning embedded block coder (SPECK) is a zero-block based coder which exploits intra-band correlation. However, they have extensively large memory requirements due to the use of three/two linked lists whose entries increase from one-bit-plane to the next. We propose an algorithm that is based on block-set partitioning and quad-splitting using two re-usable lists. The main list is initialized at the beginning of each bit-plane and is exhausted within the same bit-plane. This makes our proposed algorithm highly memory efficient. Experimental results show that the compression efficiency of the proposed method is comparable to any state-of-the-art image coder while reducing the memory requirement by 50-60% in comparison to the SPIHT algorithm.

Due to the use of variable length code (VLC), a single bit error in the discrete cosine transform (DCT)-based coded bit stream, such as H.263, may propagate up to the end of the group of blocks (GOBs) or slice. In this paper, we propose an iterative error detection and correction algorithm for the slice mode of the H.263 bit stream. The visibly erroneous macroblocks (MBs) in the decoded frames are detected by checking a set of error detection conditions derived from the redundant information (such as neighboring MBs and inner-DCT block similarity measure) inherent within the frame. In each slice, the part of the bit stream before the first erroneous MB is decoded in the conventional manner. The remaining part after this MB is redecoded iteratively, skipping one bit at a time until a decodable subbit stream is found. In case an MB is nondecodable, it is replaced with gray level. Once all the slices are checked, the frame is reconstructed and again checked for erroneous MBs. This process is repeated until the decoder detects no more corrupted MB. The proposed step-by-step decoding technique limits the error into a few MBs only, which can easily be concealed by any error concealment technique. The simulation results demonstrate that our scheme can recover the corrupted frames under the bit error rates up to 1% over binary symmetric channel (BSC), and improve the concealed picture quality by 4-6 dB over the conventional methods.

This paper proposes using a novel region space technique to track sport persons for the purpose of extracting their shirt numbers and use this to provide augmented information to the viewer. The region adjacency graph and picture trees are used to perform a search for an object using prior knowledge from a scene description. Once the candidate object has been extracted the sub-space is examined for alphanumeric characters, which are then characterized by optical character recognition. Rogue candidates may be removed based on the recognition histograms with improved robustness using temporal analysis.

This paper proposes an efficient extension of virtual set partitioning in hierarchical trees (VSPIHT) for color image coding. Our new scheme, Color-Virtual-SPIHT (CVSPIHT) generates fully embedded bit stream similar to SPIHT. It combines the zerotrees of three color planes in two steps. First, zerotrees within the same color planes are joined together by VSPIHT, then resulting longer zerotrees of three planes are combined through a novel composite tree. The simulation results show the improved performance of the proposed method compared to a SPIHT based color coding scheme.

This paper presents a novel scheme to improve the robustness of set partitioning in hierarchical tree (SPIHT) based color image coder for transmission over noisy channels. In this scheme, the SPIHT bit streams are re-arranged according to their spatial (square block) representation without loss of coding efficiency. A group of blocks, called slice are transmitted independently. The first erroneous block in the erroneous slice is detected by examining error-checking conditions while decoding the image. If any transmission error is detected, a sequence of bit skipping and redecoding process is performed on the corrupted part of the bit stream until a feasible solution is found. The simulation results show significant quality improvement.

This paper proposes a wavelet based efficient and embedded color image coding technique. It extends the use of virtual set partitioning in hierarchical trees (VSPIHT) for color images. In this technique the coefficients of chrominance planes are linked together through composite trees having roots in the virtual LL band of luminance component. The virtual decomposition is performed in the luminance plane only. The simulation results show the improved performance of the proposed technique compared to the color SPIHT (CSPIHT) as well as the technique which uses virtual decomposition in each of the color planes.