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

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.

Image and Video Compression: A Review

1997 ◽  
Vol 08 (01) ◽  
pp. 119-177 ◽  
Author(s):  
Christine I. Podilchuk ◽  
Robert J. Safranek
Keyword(s):  
Image Compression ◽  
Visual System ◽  
Video Compression ◽  
Image Coding ◽  
Human Visual System ◽  
Bit Rate ◽  
Low Bit Rate ◽  
Wide Range ◽  
Coding Standards ◽  
Image And Video Compression

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.

A New Medical Image Enhancement Method Based on Human Visual Characteristics

2014 ◽  
Vol 543-547 ◽  
pp. 2543-2546
Author(s):  
Ai Bin Dong ◽  
Yun Feng Zhang ◽  
Yi Fang Liu
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Human Visual System ◽  
Medical Image ◽  
Region Of Interest ◽  
Enhancement Method ◽  
Visual Characteristics ◽  
Medical Image Enhancement ◽  
Human Visual Characteristics

Studying of image enhancement shows that the quality of image heavily relies on human visual system. In this paper, we apply this fact to design a new image enhancement method for medical images that improves the detail regions. First, the eye region of interest (ROI) is segmented; then the Un-sharp Masking (USM) is used to enhance the detail regions. Experiments show that the proposed method can effectively improve the accuracy of medical image enhancement and has a significant effect.

The Improved Binary Tree Vector Quantization Using Spatial Sensitivity of HVS

2005 ◽  
Vol 277-279 ◽  
pp. 254-258
Author(s):  
Nae Joung Kwak ◽  
Soung Pil Ryu ◽  
Heak Bong Kwon ◽  
Jae Hyeong Ahn
Keyword(s):  
Visual System ◽  
Vector Quantization ◽  
Human Visual System ◽  
Binary Tree ◽  
Visual Quality ◽  
Special Consideration ◽  
Test Results ◽  
Spatial Sensitivity ◽  
Conventional Methods

In this paper, we proposed an improved binary tree vector quantization in special consideration of the area of spatial sensitivity which is an important characteristic of the human visual system. We regarded spatial sensitivity as a function of the human visual system, which works using variations of the three primary colors in blocks of input images. In addition, we applied the weight derived from HVS spatial sensitivity to the process of splitting nodes using eigenvectors in binary tree vector quantization. The test results showed that the proposed method provided better visual quality and greater PSNR than conventional methods.

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