An Improved 2D Histogram Infrared Image Contrast Enhancement Algorithm

Infrared imaging technology has been widely used in many fields due to its advantages such as strong anti-interference,good confidentiality,and all-weather work.However,due to the limitations of atmospheric attenuation and manufacturing processes,infrared images have low contrast.It is difficult to directly use it for eye observation,and an enhancement algorithm is needed to improve the contrast of the image to improve the visual effect.Traditional enhancement algorithms have a better effect on improving the global contrast of images,but the ability to improve the details of images is limited.The combination of global and local enhancement to improve global contrast and enhance the details of textures has gradually become one of the research hotspots in the field of enhancement processing.Existing global and local combined enhancement algorithms have problems such as insufficient global contrast enhancement and uneven distribution of fusion methods.In response to these problems,This paper proposes an improved infrared image contrast enhancement algorithm based on 2D histogram.First,this paper uses 2D histograms instead of traditional histograms.2D histograms measure the distribution of adjacent areas of a pixel,so the 2D histogram can better reflect the true distribution of the image;Secondly,in the process of correcting the 2D histogram,a new threshold value method is selected in this paper.The threshold value is calculated in consideration of the effective gray level in the current scene.The part of the threshold value is redistributed according to the proportion of elements in the 2D histogram;Finally,for the fusion method of global enhanced image and local enhanced image,this paper chooses fractional differential operator to detect the edge of the image.In order to obtain a more complete and true edge image,this paper uses the image gradient,information entropy and root mean square information to construct an adaptive order model.The global and local enhanced images are fused and output using edge images.Finally,this article chooses to compare and analyze the performance of the proposed algorithm and the comparison algorithms from two aspects: subjective visual effects and objective evaluation criteria.Experimental results show that the algorithm in this paper has achieved good results in enhancing the global contrast of images and improving detailed texture information.