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Self-adaptive gray-scale image enhancement system

A grayscale image and enhancement system technology, applied in the field of image processing, can solve the problems of non-optimal enhancement results and poor operating efficiency, and achieve the effects of improved convergence, good enhancement effect, and faster operation speed

Inactive Publication Date: 2017-10-20
ZHEJIANG UNIV
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Problems solved by technology

[0004] In order to overcome the shortcomings of non-optimal enhancement results and poor operating efficiency in the current grayscale image enhancement methods, the purpose of the present invention is to provide an adaptive grayscale image enhancement system with good enhancement effect and high operating efficiency

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Embodiment Construction

[0036] The present invention will be described in detail below according to the accompanying drawings.

[0037] refer to figure 1 , an adaptive grayscale image enhancement system, including four modules: image reading module 1, image preprocessing module 2, parameter optimization module 3, and image enhancement and output module 4, wherein:

[0038] The image reading module 1 reads in a grayscale image I with M×N pixels, and inputs it into the image preprocessing module 2 . Grayscale image I={f(x,y)}, where x=1,2,...,M, y=1,2,...,N, f(x,y) represents the pixel point (x,y) Gray value, f(x,y)∈[L min , L max ], L min , L maxRespectively represent the minimum value and maximum value of the gray value of the grayscale image read in.

[0039] After the image preprocessing module 2 normalizes the read-in grayscale image, the result is input into the parameter optimization module 3 . The purpose of image normalization is to adapt to the subsequent image enhancement transformati...

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Abstract

The invention discloses a self-adaptive gray-scale image enhancement system. The system comprises an image reading module, an image pre-processing module, a parameter optimization module and an image enhancement and output module. In the system, an input gray-scale image is firstly normalized; then the gray-scale image is enhanced by use of a transformation formula, and parameters in the transformation formula are determined through an improved intelligent optimization method. A grouping operation is added in the improved optimization method and the local optimum can be prevented in the optimization process; meanwhile, in the improved optimization method, a compressibility factor in the formula is updated and changes adaptively according to iteration count, and the convergence performance of the algorithm is improved. By use of the improved intelligent optimization method, the system can rapidly and accurately determine the optimal parameter, then carries out the enhancement operation on the gray-scale image and finally outputs the gray-scale image. The system has the characteristics of good enhancement effect and high running efficiency.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an adaptive grayscale image enhancement system. Background technique [0002] Image enhancement is an important branch of image processing. Its purpose is to improve the visual effect of the image. For the application of a given image, it aims to emphasize the overall or local characteristics of the image, to make the original unclear image clear or to emphasize a certain image. Some features of interest, expand the difference between different object features in the image, suppress uninteresting features, improve image quality, enrich information, enhance image interpretation and recognition, and meet the needs of some special analysis. [0003] Image enhancement techniques are divided into two categories: spatial domain methods and frequency domain methods. Spatial domain methods include contrast boosting, histogram equalization, histogram transformation, and optimiza...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20008G06T5/92
Inventor 刘兴高蒋雅萍王雅琳阳春华桂卫华刘平王忠徐盛虎覃伟中陈齐全谢道雄
Owner ZHEJIANG UNIV
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