Image enhancement algorithm comparison

• Main Authors: Agustin, Charina B., Dela Cruz, Rizalyn C., Go, Lilibeth L., Romero, Marianna S.
• Format: text
• Language: English
• Published: Animo Repository 1994
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/16594
• Institution: De La Salle University

The Image Enhancement Algorithm Comparison System (IEACS) is designed to compare four enhancement algorithms based on the system’s criteria. Each algorithm is performed on a saved deficient image after which the resulting image is related. Finally, this thesis involves conducting a study to determine the feasibility of the system’s criteria. The enhancement methods utilized by IEACS are contrast stretching, histogram equalization, median filtering and hi-boost filtering. The criteria includes the edge detection error rate, standard mean square error, signal-to-noise ratio and color difference measure. It refers to an original image, or a 2clear3 version of the deficient image, as basis. Through this study, it may be concluded that the effectivity of an enhancement algorithm is dependent on the type of distortion present in an image. Contrast stretching and histogram equalization correct poor contrast in an image. Median filtering is good for speckled images. Hi-boost filtering is recommended for images with unsharp edges. Finally, the criteria is not feasible because no definite correlation exists between this and the human means of image perception and judgement. The criteria is dependable only for specific cases such as neglecting the edge detection error rate for images with poor contrast and including this criterion for evaluating blurred images.