Pre-processing Image using Brightening, CLAHE and RETINEX
This work addresses image enhancement for training, but it is incremental as it compares existing methods without introducing new techniques.
The paper evaluated three image pre-processing methods (Brightening, CLAHE, and Retinex) for edge enhancement, finding that CLAHE was most effective, Brightening had little effect, and Retinex reduced sharpness, based on Canny edge detection and true positive pixel comparisons.
This paper focuses on finding the most optimal pre-processing methods considering three common algorithms for image enhancement: Brightening, CLAHE and Retinex. For the purpose of image training in general, these methods will be combined to find out the most optimal method for image enhancement. We have carried out the research on the different permutation of three methods: Brightening, CLAHE and Retinex. The evaluation is based on Canny Edge detection applied to all processed images. Then the sharpness of objects will be justified by true positive pixels number in comparison between images. After using different number combinations pre-processing functions on images, CLAHE proves to be the most effective in edges improvement, Brightening does not show much effect on the edges enhancement, and the Retinex even reduces the sharpness of images and shows little contribution on images enhancement.