A dynamic range compression algorithm of infrared image based on neighborhood feature

Abstract

Dynamic range compression and contrast enhancement are the key steps of infrared imaging. Reasonable dynamic range compression should not destroy the gray distribution relationship between adjacent pixels. Most of the existing dynamic range compression algorithms do not take maintaining the gray distribution relationship between adjacent pixels as the basic principle of algorithm design. After dynamic range compression, the gray distribution of adjacent pixels can not be consistent with that before compression, which may lead to gradient reversal, edge halo, and some algorithms have the problem that the whole image is smooth, but the details are lost seriously. An infrared image dynamic range compression algorithm with the characteristics of neighborhood gra y distribution preservation is proposed based on the principle of keeping the gray distribution of neighboring pixels. The algorithm is based on the commonly used segmented linear transformation algorithm. In order to minimize the loss of image details in dynamic range compression, local factors are introduced into the global transformation to reduce the loss of overall image details. The specific method is to add the description operator of gray distribution of adjacent pixels in the calculation of transformation parameters. The algorithm effectively improves the image details, and can obtain good display effect for the original infrared image with high dynamic range. The experimental results show that the algorithm is better than the segmented linear transformation algorithm in displaying the original infrared image with high dynamic range.