Using weighted dynamic range for histogram equalization to improve the image contrast

Abstract

In this paper, an effective method, named the brightness preserving weighted dynamic range histogram equalization (BPWDRHE), is proposed for contrast enhancement. Although histogram equalization (HE) is a universal method, it is not suitable for consumer electronic products because this method cannot preserve the overall brightness. Therefore, the output images have an unnatural looking and more visual artifacts. An extension of the approach based on the brightness preserving bi-histogram equalization method, the BPWDRHE used the weighted within-class variance as the novel algorithm in separating an original histogram. Unlike others using the average or the median of gray levels, the proposed method determined gray-scale values as break points based on the within-class variance to minimize the total squared error of each sub-histogram corresponding to the brightness shift when equalizing them independently. As a result, the contrast of both overall image and local details was enhanced adequately. The experimental results are presented and compared to other brightness preserving methods.

Fractional-order 4D hyperchaotic memristive system and application in color image encryption

“…where x, y, z and w are the stateful variables of chaotic system, q(0 < q ≤ 1) is the order of fractional-order differential equation, where W(w) is defined as W(w) = a + 3bw 2 , and a, b, α, β, γ, and ρ are the system parameters.…”

“…Nowadays, digital image is an improtant carrier of information, because of the inherent performance of digital images, including bulk data capacity, high redundancy and extremely strong correlation in adjacent pixels, which make digital image processing a research hotspot. For example, prediction error preprocessing for image compression [1], histogram equalization of images [2], image compression and reconstruction [3], and so on. To achieve the requirement of digital image safety transmission, researchers are interested in an encryption algorithm based on a chaotic system.…”

Intelligent Based Image Enhancement using Direct and In-Direct Contrast Enhancement Techniques – A Comparative Survey

“…Methods like RLBHE [19], AIEBHE [33] and BPWRDRHE [35] resulted in better image quality and increased feature information but with an overhead of computational cost of calculating thresholds. To avoid high computational cost of algorithm complexity, linear scaling [31] was adopted.…”

“…Preserving Weighted Dynamic Range Histogram Equalization (BPWRDRHE) [35] Histogram is separated based on Otsu"s method -identifying separation points using minimum class of variance forming subhistograms.…”

Image enhancement using local intensity distribution equalization

“…Singh and Kapoor [16] selects the threshold according to the exposure of the image. Recent work by Huynh-The et al [17] carefully analyzes within-class variance of each interval in order to minimize the total squared error of each sub-histogram when equalizing them independently.…”