Ring Segmented and Block Analysis Based Multi-feature Evaluation Model for Contrast Balancing

Image capturing in different indoor and outdoor environment requires high quality and sensing camera devices. Image capture in fog, night, rainy atmosphere, etc., can face an unequal contrast problem. Visibility is the primary concern for any image processing application to extract the content information and features accurately. In this paper, a ring segment based block feature evaluation method is provided to setup the enhancement individually in each segmented region. In this model, an intelligent method is applied to raw image to locate the regions with extreme visibility difference. The ring specific geographical mapping is applied to locate these regions. Three blocks from the region are evaluated based on visibility, entropy and frequency parameters. The comparative evaluation on block content strength is applied to get the referenced block blocks with maximum containment. Finally, each region block is mapped to this reference block to stabilize the contrast unbalancing. The proposed method is applied in real time captured images with different lighting effects. The comparative evaluation against histogram equalization method is applied for the PSNR and MSE parameters. The evaluation results show that the proposed method enhanced the visible quality and error robustness of dark, dull and faded images.