Noise free image restoration using hybrid filter with adaptive genetic algorithm. (August 2016)

• Record Type: Journal Article
• Authors: Sakthidasan @ Sankaran, K.; Velmurugan Nagappan, N.
• Is Part Of: Computers & electrical engineering. Volume 54(2016)
• Page Start: 382
• Page End: 392
• Publication Date: 2016-08
• Subjects: Image denoising -- Image restoration -- Genetic algorithm -- Median filter -- Bilateral filter -- Adaptive genetic algorithm; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2015.12.011
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: We modelled a Hybrid filter with AGA to remove the noise from the images. The noisy free images are restored by shining the pixel values using AGA. The performance is analysed by taking number of images and comparing the result with existing technique. Abstract: Removal of noise and restoration of images has been one of the most interesting researches in the field of image processing in the past few years. Existing filter-based methods can remove image noise; however, they cannot preserve image quality and information such as lines and edges. The proposed noise reduction image restoration technique initially performs noise removal by employing a hybrid denoising filter with an adaptive genetic algorithm. The performance of the proposed technique is evaluated by comparing the result for the proposed technique with existing denoising filters, and genetic algorithm and particle swarm optimisation methods. The comparison results show that the proposed method achieves higher-quality denoising and a high restoration ratio for noisy images than the existing methods. Graphical abstract: