Research on Image Contrast Enhancement Algorithm Based on Normalized Scalar Weight Map Coupled Fusion Pyramid

In order to solve defects such as color change and over-enhancement in the image texture or high signal activity area, as well as can not be both global content enhancement and local details enhancement by the current contrast enhancement algorithm, this paper proposed the image contrast enhancement algorithm based on normalized scalar weight map coupled fusion pyramid. It used the 2D direction of partial derivative, and defined the contrast and brightness metric model; and constructed the scalar weight map by these two models. Then it introduced the Laplacian pyramid decomposition mechanism to obtain the hierarchical structure of image; and embedded Gauss pyramid decomposition to produce the Gaussian pyramid of weight mapping. By defining fusion rules of the two pyramids, it got the fusion pyramid. Finally, by the fusion pyramid under the guide of image measurement and weight mapping model, it finished the image reconstruction. Experiments results show that the contrast enhancement quality of this algorithm is best to eliminate the introduction of transition enhancement and artificial saturation, as well as not affect the color balance comparison with current contrast enhancement algorithm.