scholarly journals Image Enhancement by High-Order Gaussian Derivative Filters Simulating Non-classical Receptive Fields in the Human Visual System

2005 ◽  
pp. 453-458 ◽  
Author(s):  
Kuntal Ghosh ◽  
Sandip Sarkar ◽  
Kamales Bhaumik
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Human Visual System ◽  
Receptive Fields ◽  
High Order ◽  
Gaussian Derivative

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.

Human Visual System Consistent Model for Wireless Capsule Endoscopy Image Enhancement and Applications

2020 ◽  
Vol 30 (3) ◽  
pp. 280-287
Author(s):  
V. B. Surya Prasath ◽  
Dang N. H. Thanh ◽  
Le Thi Thanh ◽  
N. Q. San ◽  
S. Dvoenko
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Capsule Endoscopy ◽  
Human Visual System ◽  
Wireless Capsule Endoscopy ◽  
Consistent Model ◽  
Wireless Capsule

Human visual-system-based image enhancement

2007 ◽  
Author(s):  
Eric J. Wharton ◽  
Karen A. Panetta ◽  
Sos S. Agaian
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Human Visual System

Retinal image enhancement based on the human visual system

2006 ◽  
Author(s):  
Kamel Belkacem-Boussaid ◽  
Balaji Raman ◽  
Gilberto Zamora ◽  
Yeshwanth Srinivasan ◽  
Sven-Erick Bursell
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Human Visual System ◽  
Retinal Image

Study on an Infrared Image Enhancement Algorithm by Using Lateral Inhibition of Human Visual System

2014 ◽  
Vol 696 ◽  
pp. 92-98
Author(s):  
Shao Sheng Dai ◽  
Qiang Liu ◽  
Hua Ming Tang ◽  
Jin Song Liu ◽  
Hai Yan Xiang
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Exponential Function ◽  
Lateral Inhibition ◽  
Human Visual System ◽  
Infrared Image ◽  
Distribution Model ◽  
Rapid Decline ◽  
Low Contrast ◽  
Enhancement Algorithm

Aiming at infrared images' disadvantages such as low contrast and blur edges, an infrared image enhancement algorithm using lateral inhibition of human visual system (HVS) is proposed. The algorithm makes use of the rapid decline properties of exponential function to reconstruct lateral inhibition coefficient distribution model based on exponential function, which could provide an obvious inhibition function and produce strong contrast between sharp edge and even part. The experimental results show that image edges are obviously highlighted, and the edge enhancement is 2 times compared with traditional balanced spacing density of gray-scale, and the PSNR is 2 times compared with traditional histogram equalization method.

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