A Histogram Equalization Method Preserving Background and Detail Information

Abstract

The invention relates to the field of digital image processing, and aims at enhancing digital image contrast ratio and weakening unfavorable influence on image quality caused by an over-enhancement effect, a halo effect and average brightness drifting. Therefore, the technical scheme adopted by the invention is a histogram equalization method for maintaining background and detail information. A histogram statistics calculation method for performing statistics on local neighborhood information is adopted so that an optimized histogram is generated. Meanwhile, degree of enhancement of the parameter adjustment contrast ratio is set. Before equalization of the histogram, a certain value of the optimized histogram is taken to perform segmentation, and then histogram equalization operation is performed respectively. The histogram equalization method is mainly applied to digital image processing.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to contrast enhancement of grayscale images in image enhancement, histogram processing and extraction and display of subsequent image information, specifically, a histogram equalization method for maintaining background and detail information. Background technique [0002] Digital image enhancement technology is an important aspect in image processing. Image enhancement can effectively highlight the features of interest in the image, weaken the secondary information, and can purposefully emphasize the overall and local information of the image. For distorted images, useful information in the image can be effectively restored; for images used in some special occasions, important details can be extracted. Therefore, image enhancement plays an important role in military, aviation, geographical and commercial applications, as well as in the extraction and clarity of infrared ima...

AI Technical Summary

Problems solved by technology

These phenomena will cause unnatural transition of brightness while the contrast of the image is improved, a large amount of noise will be enhanced unnecessarily, the visual effect of the image will decrease, the average brightness will drift, and the image will be distorted.

When local histogram equalization is used, the checkerboard effect of the image is too obvious, which affects the aesthetics of the overall image

This effect cannot be completely eliminated, especially at the edges

In addition, multiple histogram statistics also increase the amount of calculation

Although the histogram equalization method of dynamic range distribution has greatly improved the visual effect of the image, it still cannot completely get rid of the disadvantages brought by the histogram equalization itself. In each dynamic range, there will still be noise and over-enhancement, etc. Defects, and the redistribution of the dynamic range will increase the amount of calculation

The above histogram equalization methods do not fully consider the detailed information of the image itself, do not preserve the local details of the image well, and do not overcome the shortcomings of histogram equalization, such as obvious over-enhancement effect, noise enhancement and halo effect.

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