Enhancement of Images using Morphological Transformation
This work addresses image enhancement for poor-contrast images, but it appears incremental as it builds on existing Weber's law and morphological transformation techniques.
This paper tackles the problem of enhancing images with poor contrast and detecting backgrounds by proposing a framework that uses two methods based on Weber's law: one analyzes image background by blocks, and the other uses morphological operations like opening and closing to define multi-background gray scale images.
This paper deals with enhancement of images with poor contrast and detection of background. Proposes a frame work which is used to detect the background in images characterized by poor contrast. Image enhancement has been carried out by the two methods based on the Weber's law notion. The first method employs information from image background analysis by blocks, while the second transformation method utilizes the opening operation, closing operation, which is employed to define the multi-background gray scale images. The complete image processing is done using MATLAB simulation model. Finally, this paper is organized as follows as Morphological transformation and Weber's law. Image background approximation to the background by means of block analysis in conjunction with transformations that enhance images with poor lighting. The multibackground notion is introduced by means of the opening by reconstruction shows a comparison among several techniques to improve contrast in images. Finally, conclusions are presented.