Enhancement of low-contrast images by internal noise-induced Fourier coefficient rooting. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Chouhan, Rajlaxmi; Biswas, P.; Jha, R.
• Is Part Of: Signal, image and video processing. Volume 9:Issue 1(2015)
• Page Start: 255
• Page End: 263
• Publication Date: 2015-12
• Subjects: Contrast enhancement -- Dynamic stochastic resonance -- Discrete Fourier transform -- Noise-enhanced image processing; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0812-2
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract This paper presents a study of noise-enhanced iterative processing on Fourier coefficients for enhancement of low-contrast images. The processing equation is derived from the concept of dynamic stochastic resonance (SR), where the presence of optimum amount of noise produces an improved performance in the system. Similar to our earlier works on SR-based contrast enhancement, noise in the current context is the internal noise inherent in an image due to insufficient illumination. Here, however, the parameter selection is done so as to achieve large noise suppression. Iteration is terminated when target performance has been achieved. It is observed that the increase in the variance of the Fourier magnitude distribution leads to an increase in the contrast of the image. The increase in the variance is analytically proven to be equivalent to the process of coefficient rooting. Comparison has been made with various state-of-the-art SR and non-SR-based techniques in spatial/frequency domains. The proposed technique has been found to give noteworthy performance for both low-contrast and dark images among the SR-based techniques. The performance is also found to be better than most of the non-SR-based techniques, in terms of contrast enhancement, perceptual quality and colorfulness.