Grayscale image enhancement method based on retina mechanism

A grayscale image and retina technology, applied in the field of computer vision, can solve the problems of blurred images, poor enhancement effect in dark areas, and inability to effectively identify large contours in dark areas, and achieve the effect of enhancing brightness and edge information.

Active Publication Date: 2015-09-16
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF7 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among the above methods: the global processing operator has the same mapping function for the entire image, but the enhancement effect on the dark area is not good; the local processing operator is easy to cause the reversal of the light and dark boundary; the Retinex method needs to perform large-scale filtering on the target image, It is easy to cause image blurring, and excessive bleaching of bright areas causes loss of imag

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Grayscale image enhancement method based on retina mechanism
  • Grayscale image enhancement method based on retina mechanism
  • Grayscale image enhancement method based on retina mechanism

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0022] The human visual system will adjust the brightness to light and dark, and the antagonism mechanism based on the center and periphery of the human eye will change the size of the antagonism with the change of contrast, which can ensure a stronger response to details under bright conditions. The dark environment is more suitable for the lower visual acuity condition at this time, based on which the method of the present invention is proposed.

[0023] Example image like image 3 As shown in a, the size of the grayscale image is 859×1155. The flow chart of the specific calculation process of our algorithm is as follows figure 2 As shown, the specific process is as follows:

[0024] Step 1. Simulate the large-scale characteristics of the horizontal cell receptive field, determine the adaptive parameters, and perform a global brightness ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical filed of computer vision and especially relates to brightness enhancement and edge enhancement of a grayscale image. The method specifically comprises the following steps: estimating global brightness and determining algorithm self-adaption parameters, generating a brightness mapping graph of the images and carrying out calculation to obtain a brightness enhancement image and carrying out edge enhancement processing. The method is characterized by, to begin with, estimating the self-adaption parameters according to the brightness distribution conditions of global dark areas; then, carrying out global brightness enhancement processing on the images and obtaining the modulation mapping graph of the whole picture through a modulation function, and carrying out calculation to obtain brightness enhancement result; and finally, realizing edge enhancement based on a dimension-self-adaptive Gaussian difference model, the model dimension being influenced by contrast ratio, and therefore, bright areas can be enhanced with finer texture information, and the dark areas can be enhanced with larger contour information. The method can enhance overall brightness and contrast of the grayscale images effectively, and the self-adaption characteristic can play a very good effect on edge enhancement of the bright and dark areas.

Description

technical field [0001] The invention belongs to the technical field of computer vision, in particular to brightness enhancement and edge enhancement of grayscale images. Background technique [0002] The information in grayscale images is mainly in terms of brightness. The large-scale brightness areas in these images determine the content information of objects, while the information of lines and points is an important boundary to distinguish between different objects. Therefore, effectively enhancing the brightness of images with low overall brightness plays an important role in target recognition and so on. [0003] At present, the more classic brightness enhancement methods include traditional global processing operators such as gamma transformation, local operators based on local templates, and the improvement of the prototype of the Retinex method based on the human retina mechanism proposed by Edwin.H.Land in 1963. Among the above methods: the global processing operat...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00
Inventor 李永杰王冲李朝义
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap