Histogram equalization is widely used for contrast enhancement in a variety of applications due to its simple function and effectiveness. Examples include medical image processing and radar signal processing. One drawback of the histogram equalization can be found on the fact that the brightness of an image can be changed after the histogram equalization, which is mainly due to the flattening property of the histogram equalization. Thus, it is rarely utilized in consumer electronic products such as TV where preserving the original input brightness may be necessary in order not to introduce unnecessary visual deterioration. This paper proposes a novel extension of histogram equalization to overcome such a drawback of histogram equalization. The essence of the proposed algorithm is to utilize independent histogram equalizations separately over two subimages obtained by decomposing the input image based on its mean with a constraint that the resulting equalized subimages are bounded by each other around the input mean. It is shown mathematically that the proposed algorithm preserves the mean brightness of a given image significantly well compared to typical histogram equalization while enhancing the contrast and, thus, provides a natural enhancement that can be utilized in consumer electronic products.

Contrast enhancement using brightness preserving bi-histogram equalization

Acquired real-time image sequences, in their original form may not have good viewing quality due to lack of proper lighting or inherent noise. For example, in X-ray imaging, when continuous exposure is used to obtain an image sequence or video, usually low-level exposure is administered until the region of interest is identified. In this case, and many other similar situations, it is desired to improve the image quality in real-time. One particular method of interest, which extensively is used for enhancement of still images, is Contrast Limited Adaptive Histogram Equalization (CLAHE) proposed in [1] and summarized in [2]. This approach is computationally extensive and it is usually used for off-line image enhancement. Because of its performance, hardware implementation of this algorithm for enhancement of real-time image sequences is sought. In this paper, a system level realization of CLAHE is proposed, which is suitable for VLSI or FPGA implementation. The goal for this realization is to minimize the latency without sacrificing precision.

Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement

In this paper, a smart contrast enhancement technique based on conventional histogram equalization (HE) algorithm is proposed. This dynamic histogram equalization (DHE) technique takes control over the effect of traditional HE so that it performs the enhancement of an image without making any loss of details in it. DHE partitions the image histogram based on local minima and assigns specific gray level ranges for each partition before equalizing them separately. These partitions further go though a repartitioning test to ensure the absence of any dominating portions. This method outperforms other present approaches by enhancing the contrast well without introducing severe side effects, such as washed out appearance, checkerboard effects etc., or undesirable artifacts.

A Dynamic Histogram Equalization for Image Contrast Enhancement

This paper describes a novel strategy to enhance underwater videos and images. Built on the fusion principles, our strategy derives the inputs and the weight measures only from the degraded version of the image. In order to overcome the limitations of the underwater medium we define two inputs that represent color corrected and contrast enhanced versions of the original underwater image/frame, but also four weight maps that aim to increase the visibility of the distant objects degraded due to the medium scattering and absorption. Our strategy is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or scene structure. Our fusion framework also supports temporal coherence between adjacent frames by performing an effective edge preserving noise reduction strategy. The enhanced images and videos are characterized by reduced noise level, better exposed-ness of the dark regions, improved global contrast while the finest details and edges are enhanced significantly. In addition, the utility of our enhancing technique is proved for several challenging applications.

Enhancing underwater images and videos by fusion

Small GTPases of the Rho family are involved in the regulation of a variety of cellular processes, such as the organization of the microfilamental network, cell-cell contact and malignant transformation. To address the question of whether Rho proteins are involved in carcinogenesis in man, we compared their expression in tumors from colon, breast and lung with that of the corresponding normal tissue originating from the same patient. As shown by Rho-specific 32P-ADP-ribosylation, as well as Western-blot analysis, the amount of RhoA protein was largely increased in all 3 types of tumors tested. The most dramatic differences in the expression of Rho GTPases were observed in breast tissue. All breast tumors analyzed showed high levels of RhoA, Rac and Cdc42 proteins, whereas in the corresponding normal tissue these Rho proteins were hardly or not detectable. Progression of breast tumors from WHO grade I to grade III was accompanied by a significant average increase in RhoA protein. Overall, increase in the amount of Rho GTPases, in particular RhoA, appears to be a frequent event in different types of human tumors. This supports the view that Rho GTPases are involved in human carcinogenesis. Int. J. Cancer 81:682–687, 1999. © 1999 Wiley-Liss, Inc.

Rho GTPases are over‐expressed in human tumors

Adaptive histogram equalization (AHE) and intensity windowing have been compared using psychophysical observer studies Experienced radiologists were shown clinical CT (computerized tomographic) images of the chest Into some of the images, appropriate artificial lesions were introduced; the physicians were then shown the images processed with both AHE and intensity windowing They were asked to assess the probability that a given image contained the artificial lesion, and their accuracy was measured The results of these experiments show that for this particular diagnostic task, there was no significant difference in the ability of the two methods to depict luminance contrast; thus, further evaluation of AHE using controlled clinical trials is indicated >

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An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement

The normal method of assigning grey levels to computed tomographic (CT) numbers in CT scan display involves interactive selection of an intensity window. This method often results in the inability to visualize different types of tissue in a single image and sometimes results in unnecessary loss of contrast sensitivity. A method is described that solves these problems by automatically adapting the assignment of displayable grey levels to CT numbers in a way that varies smoothly across the image according to local needs for the presentation of contrast. The adaptation is based on local histogram equalization implemented using interpolation so as to operate on a minicomputer in a few tens of seconds. This contrast enhancement is followed by a mapping that causes the viewer's perceptual response to be linear across the display scale.

Edward V. Staab

Papers

An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement

Adaptive grey level assignment in CT scan display.

Role of gallium 67 in inflammatory disease

Computed tomography: a three-dimensional study of the nasal airway.

A method for three-dimensional image reformation for quantitative cephalometric analysis