Open AccessImage resolution and contrast enhancement with optimal brightness compensation using wavelet transforms and particle swarm optimization
Author(s) -
Tirumani V Hyma Lakshmi,
Tenneti Madhu,
K Ch. Srikavya,
Kotamraju Sarat Kumar
Publication year - 2021
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/ipr2.12268
Subject(s) - artificial intelligence , adaptive histogram equalization , computer vision , contrast (vision) , particle swarm optimization , histogram equalization , brightness , interpolation (computer graphics) , computer science , discrete wavelet transform , mathematics , pattern recognition (psychology) , wavelet transform , wavelet , histogram , image (mathematics) , algorithm , optics , physics
Improving the image resolution and contrast along with uniform brightness distribution over the entire image helps to retrieve the vital realistic information necessary for human perception and interpretation. A new procedure to improve these parameters is implemented and tested. Initially, the image is super resolute using discrete wavelet transform (DWT), stationary wavelet transform (SWT) image decomposition and bicubic interpolation. The resolute image is used for contrast enhancement by using SWT and contrast limited adaptive histogram equalization (CLAHE) approach. The optimized brightness compensation technique, which uses particle swarm optimization (PSO), is applied to the resolution and contrast‐enhanced image to obtain uniform brightness distribution over the entire image. The proposed approach is tested on three data sets of images and it is found that the visual results, as well as the resolution and contrast levels of the tested images, are significantly superior to subjective and objective results.