The Improved Binary Tree Vector Quantization Using Spatial Sensitivity of HVS

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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The Improved Binary Tree Vector Quantization Using Spatial Sensitivity of HVS

Key Engineering Materials - On the Convergence of Bio-, Information-, Enrivonmental-, Energy-, Space- and Nano-Technolgies ◽

10.4028/0-87849-958-x.254 ◽

2005 ◽

pp. 254-258

Author(s):

Nae Joung Kwak ◽

Soung Pil Ryu ◽

Heak Bong Kwon ◽

Jae Hyeong Ahn

Keyword(s):

Vector Quantization ◽

Binary Tree ◽

Spatial Sensitivity

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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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The Improved Binary Tree Vector Quantization Using Spatial Sensitivity of HVS

The KIPS Transactions PartB ◽

10.3745/kipstb.2004.11b.1.021 ◽

2004 ◽

Vol 11B (1) ◽

pp. 21-26

Keyword(s):

Vector Quantization ◽

Binary Tree ◽

Spatial Sensitivity

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Perceptual Data Hiding in Still Images

Multimedia Security ◽

10.4018/978-1-59140-192-6.ch002 ◽

2005 ◽

pp. 48-74

Author(s):

Mauro Barni ◽

Franco Bartolini ◽

Alessia De Rosa

Keyword(s):

Visual System ◽

Digital Media ◽

Data Hiding ◽

Human Visual System ◽

Visual Quality ◽

Human Vision ◽

Still Images ◽

Mandatory Requirement ◽

The Media

The idea of embedding some information within a digital media, in such a way that the inserted data are intrinsically part of the media itself, has aroused a considerable interest in different fields. One of the more examined issues is the possibility of hiding the highest possible amount of information without affecting the visual quality of the host data. For such a purpose, the understanding of the mechanisms underlying Human Vision is a mandatory requirement. Hence, the main phenomena regulating the Human Visual System will be firstly discussed and their exploitation in a data hiding system will be then considered.

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