Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

A Real-time Rate-distortion Oriented Joint Video Denoising and Compression Algorithm

This thesis proposes a real-time video denoising filter, a joint pre-filtering and compression algorithm, and a joint in-loop filtering and compression algorithm. A real-time video denoising filter: a great number of digital video applications motivate the research in restoration or enhancement methods to improve the visual quality in the presence of noise. Video Block-Matching and 3D collaborative filter, abbreviated as VBM3D, is one of the best current video denoising filters. We accelerate this filter for real-time applications by simplifying the algorithm as well as optimizing the codes, while preserving its good denoising performance. A joint pre-filtering and compression algorithm: pre-filtering and compression are two separate processes in traditional systems and they do not guarantee optimal filtering and quantization parameters with respect to rate-distortion framework. We propose a joint approach with pre-filtering by VBM3D and compression by H.264/AVC. For each quantization parameter, it jointly selects the optimal filtering parameter among the provided filtering parameters. Results show that this approach enhances the performance of H.264/AVC by improving subjective visual quality and using less bitrates. A joint in-loop filtering and compression algorithm: in traditional video in-loop filtering and compression systems, a deblocking filter is employed in both the encoder and decoder. However, besides blocking artifacts, videos may contain other types of noise. In order to remove other types of noise, we add a real-time filter as an enhancing part in the H.264/AVC codec after the deblocking filter. Experiments illustrate that the proposed algorithm improves the compression performance of the H.264/AVC standard by providing frames with increased PSNR values and less bitrates. /Kir1

ChitChat: Making Video Chat Robust to Packet Loss

Video chat is increasingly popular among Internet users. Often, however, chatting sessions suffer from packet loss, which causes video outage and poor quality. Existing solutions however are unsatisfying. Retransmissions increase the delay and hence can interact negatively with the strict timing requirements of interactive video. FEC codes introduce extra overhead and hence reduce the bandwidth available for video data even in the absence of packet loss. This paper presents ChitChat, a new approach for reliable video chat that neither delays frames nor introduces bandwidth overhead. The key idea is to ensure that the information in each packet describes the whole frame. As a result, even when some packets are lost, the receiver can still use the received packets to decode a smooth version of the original frame. This reduces frame loss and the resulting video freezes and improves the perceived video quality. We have implemented ChitChat and evaluated it over multiple Internet paths. In comparison to Windows Live Messenger 2009, our method reduces the occurrences of video outage events by more than an order of magnitude

Mitigation of H.264 and H.265 Video Compression for Reliable PRNU Estimation

The photo-response non-uniformity (PRNU) is a distinctive image sensor characteristic, and an imaging device inadvertently introduces its sensor's PRNU into all media it captures. Therefore, the PRNU can be regarded as a camera fingerprint and used for source attribution. The imaging pipeline in a camera, however, involves various processing steps that are detrimental to PRNU estimation. In the context of photographic images, these challenges are successfully addressed and the method for estimating a sensor's PRNU pattern is well established. However, various additional challenges related to generation of videos remain largely untackled. With this perspective, this work introduces methods to mitigate disruptive effects of widely deployed H.264 and H.265 video compression standards on PRNU estimation. Our approach involves an intervention in the decoding process to eliminate a filtering procedure applied at the decoder to reduce blockiness. It also utilizes decoding parameters to develop a weighting scheme and adjust the contribution of video frames at the macroblock level to PRNU estimation process. Results obtained on videos captured by 28 cameras show that our approach increases the PRNU matching metric up to more than five times over the conventional estimation method tailored for photos

Making video chat robust to packet loss

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 77-83).Video chat is increasingly popular among Internet users (e.g. Skype, Windows Live Messenger, Google Talk). Often, however, chatting sessions suffer from packet loss, which causes video outage and poor quality. Existing solutions however are unsatisfying. Retransmissions increase the delay and hence can interact negatively with the strict timing requirements of interactive video. FEC codes introduce extra overhead and hence reduce the bandwidth available for video data even in the absence of packet loss. In this thesis, we present ChitChat, a new approach for reliable video chat that neither delays frames nor introduces bandwidth overhead. The key idea is to ensure that the information in each packet describes the whole frame. As a result, even when some packets are lost, the receiver can still use the received packets to decode a smooth version of the original frame. This reduces frame loss and the resulting video freezes and improves the perceived video quality. We have implemented ChitChat and evaluated it over multiple Internet paths. In comparison to Windows Live Messenger 2009, our method reduces the occurrences of video outage events by more than an order of magnitude.by Jue Wang.S.M

Study and Implementation of Watermarking Algorithms

Water Making is the process of embedding data called a watermark into a multimedia object such that watermark can be detected or extracted later to make an assertion about the object. The object may be an audio, image or video. A copy of a digital image is identical to the original. This has in many instances, led to the use of digital content with malicious intent. One way to protect multimedia data against illegal recording and retransmission is to embed a signal, called digital signature or copyright label or watermark that authenticates the owner of the data. Data hiding, schemes to embed secondary data in digital media, have made considerable progress in recent years and attracted attention from both academia and industry. Techniques have been proposed for a variety of applications, including ownership protection, authentication and access control. Imperceptibility, robustness against moderate processing such as compression, and the ability to hide many bits are the basic but rat..

JOINT CODING OF MULTIMODAL BIOMEDICAL IMAGES US ING CONVOLUTIONAL NEURAL NETWORKS

The massive volume of data generated daily by the gathering of medical images with different modalities might be difficult to store in medical facilities and share through communication networks. To alleviate this issue, efficient compression methods must be implemented to reduce the amount of storage and transmission resources required in such applications. However, since the preservation of all image details is highly important in the medical context, the use of lossless image compression algorithms is of utmost importance. This thesis presents the research results on a lossless compression scheme designed to encode both computerized tomography (CT) and positron emission tomography (PET). Different techniques, such as image-to-image translation, intra prediction, and inter prediction are used. Redundancies between both image modalities are also investigated. To perform the image-to-image translation approach, we resort to lossless compression of the original CT data and apply a cross-modality image translation generative adversarial network to obtain an estimation of the corresponding PET. Two approaches were implemented and evaluated to determine a PET residue that will be compressed along with the original CT. In the first method, the residue resulting from the differences between the original PET and its estimation is encoded, whereas in the second method, the residue is obtained using encoders inter-prediction coding tools. Thus, in alternative to compressing two independent picture modalities, i.e., both images of the original PET-CT pair solely the CT is independently encoded alongside with the PET residue, in the proposed method. Along with the proposed pipeline, a post-processing optimization algorithm that modifies the estimated PET image by altering the contrast and rescaling the image is implemented to maximize the compression efficiency. Four different versions (subsets) of a publicly available PET-CT pair dataset were tested. The first proposed subset was used to demonstrate that the concept developed in this work is capable of surpassing the traditional compression schemes. The obtained results showed gains of up to 8.9% using the HEVC. On the other side, JPEG2k proved not to be the most suitable as it failed to obtain good results, having reached only -9.1% compression gain. For the remaining (more challenging) subsets, the results reveal that the proposed refined post-processing scheme attains, when compared to conventional compression methods, up 6.33% compression gain using HEVC, and 7.78% using VVC