Image and Video Compression: A Review

The area of image and video compression has made tremendous progress over the last several decades. The successes in image compression are due to advances and better understanding of waveform coding methods which take advantage of the signal statistics, perceptual methods which take advantage of psychovisual properties of the human visual system (HVS) and object-based models especially for very low bit rate work. Recent years have produced several image coding standards—JPEG for still image compression and H.261, MPEG-I and MPEG-II for video compression. While we have devoted a special section in this paper to cover international coding standards because of their practical value, we have also covered a large class of nonstandard coding technology in the interest of completeness and potential future value. Very low bit rate video coding remains a challenging problem as does our understanding of the human visual system for perceptually optimum compression. The wide range of applications and bit rates, from video telephony at rates as low as 9.6 kbps to HDTV at 20 Mbps and higher, has acted as a catalyst for generating new ideas in tackling the different challenges characterized by the particular application. The area of image compression will remain an interesting and fruitful area of research as we focus on combining source coding with channel coding and multimedia networking.

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Low bit rate image coding technique using human visual system model and homomorphic processing

Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation ◽

10.1109/tencon.1993.328002 ◽

2002 ◽

Author(s):

L.K. Ho ◽

T.S. Ng

Keyword(s):

Visual System ◽

Image Coding ◽

Human Visual System ◽

System Model ◽

Bit Rate ◽

Low Bit Rate

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A Perceptually Optimized Foveation Wavelet Visible Difference Predictor Quality Metric Based on Psychovisual Properties of the Human Visual System (HVS)

Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-7998-4444-0.ch014 ◽

2020 ◽

pp. 268-281

Author(s):

Abderrahim Bajit

Keyword(s):

Visual System ◽

Video Compression ◽

Image Coding ◽

Human Visual System ◽

Quality Measurement ◽

Region Of Interest ◽

Visual Quality ◽

Perceptual Quality ◽

Foveated Imaging ◽

Error Perception

Region of interest (ROI) image and video compression techniques have been widely used in visual communication applications in an effort to deliver good quality images and videos at limited bandwidths. Foveated imaging exploits the fact that the spatial resolution of the human visual system (HVS) is highest around the point of fixation (foveation point) and decreases dramatically with increasing eccentricity. Exploiting this fact, the authors have developed an appropriate metric for the assessment of ROI coded images, adapted to foveation image coding based on psycho-visual quality optimization tools, which objectively enable us to assess the visual quality measurement with respect to the region of interest (ROI) of the human observer. The proposed metric yields a quality factor called foveation probability score (FPS) that correlates well with visual error perception and demonstrating very good perceptual quality evaluation.

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HVS-Based Low Bit-Rate Image Compression

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.511-512.441 ◽

2014 ◽

Vol 511-512 ◽

pp. 441-446

Author(s):

Yuer Wang ◽

Zhong Jie Zhu ◽

Wei Dong Chen

Keyword(s):

Image Compression ◽

Image Coding ◽

Rate Distortion ◽

Binary Image ◽

Perceptual Quality ◽

Hybrid Architecture ◽

Bit Rate ◽

Low Bit Rate ◽

Heat Transfer Theory ◽

Key Techniques

Image coding and compression is one of the most key techniques in the area of image signal processing, However, most of the existing coding methods such as JPEG, employ the similar hybrid architecture to compress images and videos. After many years of development, it is difficult to further improve the coding performance. In addition, most of the existing image compression algorithms are designed to minimize difference between the original and decompressed images based on pixel wise distortion metrics, such as MSE, PSNR which do not consider the HVS features and is not able to guarantee good perceptual quality of reconstructed images, especially at low bit-rate scenarios. In this paper, we propose a novel scheme for low bit-rate image compression. Firstly, the original image is quantized to a binary image based on heat transfer theory. Secondly, the bit sequence of the binary image is divided into several sub-sets and each one is designated a priority based on the rate-distortion principle. Thirdly, the sub-sets with high priorities are selected based on the given bit-rate. Finally, the context-based binary arithmetic coding is employed to encode the sub-sets selected to produce the final compressed stream. At decoder, the image is decoded and reconstructed based on anisotropic diffusion. Experiments are conducted and provide convincing results.

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Low bit-rate compression of underwater image based on human visual system

Signal Processing Image Communication ◽

10.1016/j.image.2020.116082 ◽

2021 ◽

Vol 91 ◽

pp. 116082

Author(s):

Fei Yuan ◽

Lihui Zhan ◽

Panwang Pan ◽

En Cheng

Keyword(s):

Visual System ◽

Human Visual System ◽

Bit Rate ◽

Low Bit Rate ◽

Underwater Image

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Objective Human Visual System Based Video Quality Assessment Metric for Low Bit-Rate Video Communication Systems

2006 IEEE Workshop on Multimedia Signal Processing ◽

10.1109/mmsp.2006.285322 ◽

2006 ◽

Cited By ~ 3

Author(s):

David Lin ◽

Paul Chau

Keyword(s):

Visual System ◽

Quality Assessment ◽

Human Visual System ◽

Communication Systems ◽

Video Quality ◽

Video Communication ◽

Video Quality Assessment ◽

Bit Rate ◽

Low Bit Rate

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Research and Progress of Image Compression Coding Based on Wavelet

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.403-408.1352 ◽

2011 ◽

Vol 403-408 ◽

pp. 1352-1355

Author(s):

Yue Li Cui ◽

Zhi Gang Chen ◽

Ai Hua Chen

Keyword(s):

Wavelet Transform ◽

Image Compression ◽

Visual System ◽

Frequency Domain ◽

Image Coding ◽

Human Visual System ◽

Original Image ◽

Local Characteristics ◽

Compression Coding ◽

Research Hotspots

Image compression is a technology using as little as possible bits to represent the original image. As wavelet transform has local characteristics on the time and frequency domain, it makes up the deficiency of DCT. Moreover, its multi-resolution characteristics can easily associate with the human visual system (HVS). Besides, wavelet-based image compression is prone to combine with new image coding methods. It has become the research hotspots at present. This paper introduces wavelets theory and discusses the research status and progress of wavelet-based image compression then points out the main problems. Finally, the prospect in the future was presented.

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