A content-aware quantisation mechanism for transform domain distributed video coding

The discrete cosine transform (DCT) is widely applied in modern codecs to remove spatial redundancies, with the resulting DCT coefficients being quantised to achieve compression as well as bit-rate control. In distributed video coding (DVC) architectures like DISCOVER, DCT coefficient quantisation is traditionally performed using predetermined quantisation matrices (QM), which means the compression is heavily dependent on the sequence being coded. This makes bit-rate control challenging, with the situation exacerbated in the coding of high resolution sequences due to QM scarcity and the non-uniform bit-rate gaps between them. This paper introduces a novel content-aware quantisation (CAQ) mechanism to overcome the limitations of existing quantisation methods in transform domain DVC. CAQ creates a frame-specific QM to reduce quantisation errors by analysing the distribution of DCT coefficients. In contrast to the predetermined QM that is applicable to only 4x4 block sizes, CAQ produces QM for larger block sizes to enhance compression at higher resolutions. This provides superior bit-rate control and better output quality by seeking to fully exploit the available bandwidth, which is especially beneficial in bandwidth constrained scenarios. In addition, CAQ generates superior perceptual results by innovatively applying different weightings to the DCT coefficients to reflect the human visual system. Experimental results corroborate that CAQ both quantitatively and qualitatively provides enhanced output quality in bandwidth limited scenarios, by consistently utilising over 90% of available bandwidth

Hierarchical Lossless Image Compression for Telemedicine Applications

AbstractThe main aim of hierarchical lossless image compression is to improve accuracy, reduce the bit rate and improve the compression efficiency for the storage and transmission of the medical images while maintain an acceptable image quality for diagnosis purpose. The cost and limitation in bandwidth of wireless channels has made compression is necessity in today's era. In medical images, the contextual region is an area which contains an important information and must be transmitted without distortion. In this paper the selected region of the image is encoded with Adaptive Multiwavelet Transform AMWT) using Multi Dimensional Layered Zero Coding (MLZC). Experimental results shows that Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), Mean Structural Similarity Index (MSSIM) performance is high and Root Mean Square Error (RMSE), Mean Absolute Error (MAE) values are low, and moderate Compression Ratio (CR) at high Bits Per Pixel (BPP) when compared to the integer wavelet and multiwavelet transform

Visual Attention for Region of Interest Coding in JPEG 2000

This paper details work undertaken on the application of an algorithm for visual attention (VA) to region of interest (ROI) coding in JPEG 2000 (JP2K). In this way, an "interest ordered" progressive bit-stream is produced where the regions highlighted by the VA algorithm are presented first in bit-stream. The paper briefly outlines the terminology used in JP2K, the packet structure of the bit-stream, and the methods available to achieve ROI coding in JP2K (tiling, coefficient scaling, and code-block selection). The paper then describes how the output of the VA algorithm is post-processed so that an ROI is produced that can be efficiently coded using coefficient scaling in JP2K. Finally, a two alternative forced choice (2AFC) visual trial is undertaken to compare the visual quality of images encoded using the proposed VA ROI algorithm and conventional JP2K. The experimental results show that, while there is no overall preference for the VA ROI encoded images; there is an improvement in perceived image quality at low bit rates (below 0.25 bits per pixel). It is concluded that an overall increase in image quality only occurs when the increase in quality of the ROI more than compensates for the decrease in quality of the image background (i.e., non-ROI)

Can Region of Interest Coding Improve Overall Perceived Image Quality?

In this paper we review a number of approaches to reducing, or removing, the problem of shift variance in the discrete wavelet transform (DWT). We describe a generalization of the critically sampled DWT and the fully sampled 'algorithme a trous' that provides approximate shift-invariance with an acceptable level of redundancy. The proposed over complete DWT (OCDWT) is critically sub-sampled to a given level of the decomposition, below which it is then fully sampled. The efficacy of the proposed algorithm is illustrated in an edge detection context and directly compared to a number of other shift-invariant transforms in terms of complexity and redundancy

Implementation of Image Compression Algorithm using Verilog with Area, Power and Timing Constraints

Image compression is the application of Data compression on digital images. A fundamental shift in the image compression approach came after the Discrete Wavelet Transform (DWT) became popular. To overcome the inefficiencies in the JPEG standard and serve emerging areas of mobile and Internet communications, the new JPEG2000 standard has been developed based on the principles of DWT. An image compression algorithm was comprehended using Matlab code, and modified to perform better when implemented in hardware description language. Using Verilog HDL, the encoder for the image compression employing DWT was implemented. Detailed analysis for power, timing and area was done for Booth multiplier which forms the major building block in implementing DWT. The encoding technique exploits the zero tree structure present in the bitplanes to compress the transform coefficients

Research and developments of distributed video coding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The recent developed Distributed Video Coding (DVC) is typically suitable for the applications such as wireless/wired video sensor network, mobile camera etc. where the traditional video coding standard is not feasible due to the constrained computation at the encoder. With DVC, the computational burden is moved from encoder to decoder. The compression efficiency is achieved via joint decoding at the decoder. The practical application of DVC is referred to Wyner-Ziv video coding (WZ) where the side information is available at the decoder to perform joint decoding. This join decoding inevitably causes a very complex decoder. In current WZ video coding issues, many of them emphasise how to improve the system coding performance but neglect the huge complexity caused at the decoder. The complexity of the decoder has direct influence to the system output. The beginning period of this research targets to optimise the decoder in pixel domain WZ video coding (PDWZ), while still achieves similar compression performance. More specifically, four issues are raised to optimise the input block size, the side information generation, the side information refinement process and the feedback channel respectively. The transform domain WZ video coding (TDWZ) has distinct superior performance to the normal PDWZ due to the exploitation in spatial direction during the encoding. However, since there is no motion estimation at the encoder in WZ video coding, the temporal correlation is not exploited at all at the encoder in all current WZ video coding issues. In the middle period of this research, the 3D DCT is adopted in the TDWZ to remove redundancy in both spatial and temporal direction thus to provide even higher coding performance. In the next step of this research, the performance of transform domain Distributed Multiview Video Coding (DMVC) is also investigated. Particularly, three types transform domain DMVC frameworks which are transform domain DMVC using TDWZ based 2D DCT, transform domain DMVC using TDWZ based on 3D DCT and transform domain residual DMVC using TDWZ based on 3D DCT are investigated respectively. One of the important applications of WZ coding principle is error-resilience. There have been several attempts to apply WZ error-resilient coding for current video coding standard e.g. H.264/AVC or MEPG 2. The final stage of this research is the design of WZ error-resilient scheme for wavelet based video codec. To balance the trade-off between error resilience ability and bandwidth consumption, the proposed scheme emphasises the protection of the Region of Interest (ROI) area. The efficiency of bandwidth utilisation is achieved by mutual efforts of WZ coding and sacrificing the quality of unimportant area. In summary, this research work contributed to achieves several advances in WZ video coding. First of all, it is targeting to build an efficient PDWZ with optimised decoder. Secondly, it aims to build an advanced TDWZ based on 3D DCT, which then is applied into multiview video coding to realise advanced transform domain DMVC. Finally, it aims to design an efficient error-resilient scheme for wavelet video codec, with which the trade-off between bandwidth consumption and error-resilience can be better balanced

MICROANGIOGRAM VIDEO COMPRESSION USING ADAPTIVE PREDICTION

Coronary angiography is an X-ray examination of the heart\u27s arteries. This is an essential technique for diagnosis of heart damages. Image sequences from digital angiography contain areas of high diagnostic interest. Loss of information due to compression for regions of interest (ROI) in angiograms is not tolerable. Since Commercially available technology such as JPEG and MPEG do not satisfy medical requirements due to their severe blockartifacts. In this paper, a new compression algorithm that achieves high compression ratio and excellent reconstruction quality for video rate or sub-video rate angiograms is developed. The proposed algorithm exploits temporal spatial and spectral redundancies in backward adaptive fashion with Extremely low side information. An experimental result shows that the proposed scheme provides significant improvements in compression efficiencies

Prioritizing Content of Interest in Multimedia Data Compression

Image and video compression techniques make data transmission and storage in digital multimedia systems more efficient and feasible for the system's limited storage and bandwidth. Many generic image and video compression techniques such as JPEG and H.264/AVC have been standardized and are now widely adopted. Despite their great success, we observe that these standard compression techniques are not the best solution for data compression in special types of multimedia systems such as microscopy videos and low-power wireless broadcast systems. In these application-specific systems where the content of interest in the multimedia data is known and well-defined, we should re-think the design of a data compression pipeline. We hypothesize that by identifying and prioritizing multimedia data's content of interest, new compression methods can be invented that are far more effective than standard techniques. In this dissertation, a set of new data compression methods based on the idea of prioritizing the content of interest has been proposed for three different kinds of multimedia systems. I will show that the key to designing efficient compression techniques in these three cases is to prioritize the content of interest in the data. The definition of the content of interest of multimedia data depends on the application. First, I show that for microscopy videos, the content of interest is defined as the spatial regions in the video frame with pixels that don't only contain noise. Keeping data in those regions with high quality and throwing out other information yields to a novel microscopy video compression technique. Second, I show that for a Bluetooth low energy beacon based system, practical multimedia data storage and transmission is possible by prioritizing content of interest. I designed custom image compression techniques that preserve edges in a binary image, or foreground regions of a color image of indoor or outdoor objects. Last, I present a new indoor Bluetooth low energy beacon based augmented reality system that integrates a 3D moving object compression method that prioritizes the content of interest.Doctor of Philosoph