A variational approach to the radiometric enhancement of digital imagery

Altas, Irfan; Louis, John; Belward, John A.

doi:10.1109/83.388088

Cited by 26 publications

(19 citation statements)

References 5 publications

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“…According to formula, (x, y) are the coordinates of the center picture element in the kernel and min and max are the minimum and maximum values of the image data in the selected kernel [13].…”

Section: Ip(x Y) Is the Color Level For The Output Pixel(x Y) Aftermentioning

confidence: 99%

Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces

ElDahshan

Youssef

Masameer

et al. 2015

JBEMi

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Image segmentation process is considered the most essential step in image analysis especially in the medical field. In this paper, the color segmentation for acute lymphoblastic leukemia images (ALL) is applied to segment each leukemia image into two clearly defined regions: blasts and background. The ALL segmentation process is based on two different color spaces: RGB color space and HSV color space. The comparison performance between the segmentation methods based on RGB and HSV color spaces are investigated to find the best method to segment the acute lymphoblastic leukemia images. The experimental results show that the segmentation of ALL images based on HSV color space yield better accuracy than RGB color space when compared with the manual segmentation image made by medical experts. Using HSV color space, the shape of blasts in ALL blood samples is closely preserved with segmentation accuracy over 99.00%. However, segmentation based HSV color space was chosen as it produced the highest ALL segmentation rate.

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Section: Ip(x Y) Is the Color Level For The Output Pixel(x Y) Aftermentioning

confidence: 99%

Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces

ElDahshan

Youssef

Masameer

et al. 2015

JBEMi

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“…In Section 2, we first introduce a variational formulation of histogram equalization proposed by Altas, Louis, and Belward [23]. By the variational approach, histogram equalization is expressed as a functional optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Image Contrast Enhancement by Constrained Local Histogram Equalization

Zhu

Chan

Lam

1999

Computer Vision and Image Understanding

130

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“…Contrast stretching methods using local statistics are also reported [16,17,24]. Attas et al [1] have devised a variational approach to local contrast enhancement through a suitable optimization of some desirable characteristics of graylevel histogram of output image. Similar approach for constrained local histogram equalization has been adopted by Zhu et al [31].…”

Section: Introductionmentioning

confidence: 99%

A multiscale morphological approach to local contrast enhancement

2000

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A scheme for enhancing local contrast of raw images based on multiscale morphology is presented in this paper. The conventional theoretical concept of local contrast enhancement has been extended in the regime of mathematical morphology. The intensity values of the scale-speci"c features of the image extracted using multiscale tophat transformation are modi"ed for achieving local contrast enhancement. Locally enhanced features are combined to reconstruct the "nal image. The proposed algorithm has been executed on a set of raw images for testing its e$cacy and the result has been compared with that of other standard methods for getting idea about its relative performance.2000 Elsevier Science B.V. All rights reserved. Zusammenfassung Re2 sume2Nous preH sentons dans cet article un scheH ma de rehaussement du contraste local dans des images, reposant sur de la morphologie multi-eH chelle. Le concept theH orique conventionne du rehaussement de contraste local a eH teH eH tendu dans le reH gime de la morphologie matheH matique. Les valeurs d'intensiteH des caracteH ristiques speH ci"ques de l'eH chelle dans l'image, extraites en utilisant la transformation du chapeau haut-de-forme multi-eH chelle, sont modi"eH es pour atteindre un rehaussement du contraste local. Less caracteH ristiques rehausseH es localement sont combineH es pour reconstruire l'image "nale. L'algorithme proposeH a eH teH exeH cuteH sur un ensemble d'images a"n de tester sont e$caciteH et les reH sultats ont eH teH 0165-1684/00/$ -see front matter 2000 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 5 -1 6 8 4 ( 9 9 ) 0 0 1 6 1 -9 compareH s avec ceux d'autres meH thodes standard a"n d'avoir une ideH e de ses performances relatives.2000 Elsevier Science B.V. All rights reserved.

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A variational approach to the radiometric enhancement of digital imagery

Cited by 26 publications

References 5 publications

Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces

Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces

Image Contrast Enhancement by Constrained Local Histogram Equalization

A multiscale morphological approach to local contrast enhancement

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