A fuzzy neural approach to novel color balance with FPGA implementation

Color balance has become an important part of image processing pipeline. It forms a class of image processing algorithms for removal of color cast in digitally captured images. This work presents a fuzzy neural approach to establish a model for estimation of adjusting ratios for the color separates of a digitally captured image based only on the contents of the image. The estimated ratios are then utilized to perform color balance for the image. The comparative study suggests that the proposed method is more adaptable to generic images and varieties of illuminants and scenes than other existing methods do. Hardware implementation of the algorithm based on FPGA is also presented in this work.