Low Contrast Image Enhancement Using Adaptive Filter and DWT: A Literature Review

Abstract Image enhancement refers to accentuation, or sharpening of image features such as edges, boundaries or contrast to make a graphic display more useful for display and analysis. One of the most common defects of photographic or digital images is poor contrast resulting from a reduced, and perhaps nonlinear, image amplitude range. This paper reviews different algorithms particularly based on adaptive filtering techniques. Weighted filter algorithm, particle swarm optimization(PSO) algorithm, algorithm using hybrid combination of particle filter and wavelet, algorithm using combination of three techniques (median filtering, CLAHE and morphological operation), local tone mapping algorithm and Non-linear adaptive (NLA) algorithm are discussed and compared. This paper concludes about better algorithm which may be the field of research. Keywords: Contrast enhancement; PSO; Adaptive filter; Discrete wavelet transform. 1. Introduction One of the most common defects of photographic or digital images is poor contrast resulting from a reduced, and perhaps nonlinear, image amplitude range 2. Literature review This paper reviews various algorithms based on adaptive filtering techniques for low contrast image enhancement. Weighted filter algorithm In this paper [1] the proposed algorithm uses a weighted filter for enhancing global brightness and contrast of images and wavelet transform to enhance the color information. The flowchart of the proposed method is shown i

Adaptive scale adjustment design of unsharp masking filters for image contrast enhancement

© 2013 IEEE. The unsharp masking filter (UMF) has been widely used in image processing front ends for contrast enhancement. The filter, being easy to implement, is based on the concept of augmenting a scaled and high-passed version of the image to itself. The UMF performance is critically dependent on the generation of the highpassed signal to be added as well as its associated scale factor. However, the optimal choice of filter parameters still remains a challenging task due to possible intensity clipping problems where the filtered pixel magnitude is vulnerable to be out of the permitted display ranges. In this research, an adaptive scheme is formulated such that the scale is derived from the pixel intensity of the input image. Specifically, pixels in the mid-range intensity will be assigned a larger scaling factor according to a Gaussian-like profile. In addition, the optimal profile coefficients and the width of the high-pass generator window are determined by adopting the particle swarm optimization algorithm. Satisfactory simulation results obtained from a collection of a large set of images have shown the effectiveness of the proposed image contrast enhancement approach