This paper makes an investigation of the dehazing effects on image and video coding for surveillance systems. The goal is to achieve good dehazed images and videos at the receiver while sustaining low bitrates (using compression) in the transmission pipeline. At first, this paper proposes a novel method for single-image dehazing, which is used for the investigation. It operates at a faster speed than current methods and can avoid halo effects by using the median operation. We then consider the dehazing effects in compression by investigating the coding artifacts and motion estimation in cases of applying any dehazing method before or after compression. We conclude that better dehazing performance with fewer artifacts and better coding efficiency is achieved when the dehazing is applied before compression. Simulations for Joint Photographers Expert Group images in addition to subjective and objective tests with H.264 compressed sequences validate our conclusion.

The paper proposes a novel method for coding artifact reduction in compressed images. For removing blocking artifacts, a localized DCT-based filter with condition on the similarity between surrounding blocks is considered. To reduce ringing, a localized fuzzy filter is utilized to avoid the blurry effect of linear filter and painting-like effect of conventional fuzzy filter. To enhance chroma components and reduce the color bleeding, the localized filter for luma component are implemented for the chroma components. Simulations on a wide range of compressed images are performed to verify the effectiveness of the algorithm.

A novel automatic video deshearing is proposed to reduce the skew artifacts (jelly artifacts) in sequences captured by CMOS censor cameras. The paper first considers the principles of skew artifacts in rolling shutter cameras. Then a deshearing algorithm with high accuracy is discussed with automatic skew artifact detection. A video completion step is also implemented to reconstruct unavailable pixels in the new grid of the desheared frame. Simulation results show that the proposed method effectively reduces the skew artifacts for different sequences captured by rolling shutter cameras.

We propose a fast subpixel motion estimation method for motion deblurring, where conventional motion estimation algorithms used in video codings are too complex. The new algorithm is a combination of block matching and optical flow. It does not require any interpolation and it does not provide motion compensated frames. Thus it is much faster than conventional methods. Statistical results show that the new algorithm performs quickly and accurately. It also demonstrates compatible performance with the benchmarking full search algorithm, yet uses significantly less amount of time.

This paper proposes a selective data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. The original frames are pruned to a smaller size before compression. After decoding, they are interpolated back to their original size by an edge-directed interpolation method. The data pruning phase is optimized to obtain the minimal distortion in the interpolation phase. Furthermore, a novel high-order interpolation is proposed to adapt the interpolation to several edge directions in the current frame. This high-order filtering uses more surrounding pixels in the frame than the fourth-order edge-directed method and it is more robust. The algorithm is also considered for multiframe-based interpolation by using spatio-temporally surrounding pixels coming from the previous frame. Simulation results are shown for both image interpolation and coding applications to validate the effectiveness of the proposed methods.

This paper proposes a data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. The original frames are pruned to a smaller size before compression. After decoding, they are interpolated to their original size by an edge-directed interpolation. The data pruning is optimized to obtain the minimal distortion in the interpolation phase. Furthermore, a novel high order interpolation is proposed to adapt the interpolation to many edge directions. This high order filtering uses extra surrounding pixels and achieves more robust edge-directed image interpolation. Simulation results are shown for both image interpolation and coding applications.

The paper proposes a novel algorithm to enhance the quality of H.264/AVC compressed video sequences by using an in-loop spatio-temporal motion compensated ??lter (MCSTF). Extra information from surrounding coded frames are used together with the information of the current coded frame to reduce the coding artifacts. With the availability of the original frame, the MCSTF coef??cients are optimized at the encoder and then are implemented at the decoder. Furthermore, an overlapped motion compensated scheme is proposed to reduce the blocking artifacts from surrounding motion compensated frames. Simulation results are judged by PSNR and ??ickering metric.

A fuzzy filter adaptive to both sample's activity and the relative position between samples is proposed to reduce the artifacts in compressed multidimensional signals. For JPEG images, the fuzzy spatial filter is based on the directional characteristics of ringing artifacts along the strong edges. For compressed video sequences, the motion compensated spatiotemporal filter (MCSTF) is applied to intraframe and interframe pixels to deal with both spatial and temporal artifacts. A new metric which considers the tracking characteristic of human eyes is proposed to evaluate the flickering artifacts. Simulations on compressed images and videos show improvement in artifact reduction of the proposed adaptive fuzzy filter over other conventional spatial or temporal filtering approaches.

We propose a directional fuzzy filter to enhance the quality of compressed video sequences. A motion compensated spatio-temporal filter (MCSTF) is applied to intra-frame and inter-frame pixels to reduce both spatial and temporal artifacts. The MCSTF is adaptive to the pixel location, the intensity and position of surrounding pixels. To evaluate the flickering artifacts, a new metric is proposed to take into account the tracking characteristic of human eyes. Simulations on H.264 compressed videos show improvement in artifact reduction of the proposed directional fuzzy filter over other conventional spatial or temporal filtering approaches.

We propose a novel method to reduce both blocking and ringing artifacts in compressed images and videos. Based on the directional characteristics of ringing artifacts along edges, we use a directional fuzzy filter which is adaptive to the direction of the ringing artifact. The filter exploits the spatial order, the rank order and the spread information of the signal together with the position of the pixels to enhance the quality of the compressed image. Simulations results on compressed images and videos having simple and complex edges show the improvement of the proposed directional fuzzy filter over the conventional fuzzy filtering and other approaches.

The paper proposes a pixel-based post-processing algorithm to enhance the quality of motion JPEG (MJPEG) by exploiting the temporal redundancies of the decoded frames. The technique permits reconstruction of the high frequency coefficients lost during quantization, thereby reducing ringing artifacts. Based on the linearization of the quantization function, the error between the estimated and original coefficients is analyzed for both cases of ideal and real video sequences. Blocking artifact reduction is verified by a reduction in the variance of this coefficient error. The condition of valid motion vectors to get quality improvement is considered based on these errors. The algorithm is also extended to find the optimal filter for a general estimation scheme based on an arbitrary number of frames. Results in visual and peak signal-to-noise ratio improvement using both integer and subpixel motion vectors are verified by simulations on video sequences.

We propose a post processing algorithm to enhance the quality of Motion JPEG (MJPEG) by exploiting temporal redundancies. The error between the estimated and original blocks is analyzed using the translational relation in the discrete cosine transform (DCT) domain. The proposed algorithm permits reconstructing the high frequency coefficients lost during quantization and therefore reduces the ringing artifact. Blocking artifact reduction is verified by the decrease in the variance of this coefficient error. Results in quality and PSNR improvement for both cases of integer and sub-pixel motion vectors are verified by simulations on video sequences.