Efficient edge-preserving algorithm for color contrast enhancement with application to color image segmentation

Chung, Kuo–Liang; Yang, Wei-Jen; Yan, Wen-Ming

doi:10.1016/j.jvcir.2008.02.002

Cited by 20 publications

(17 citation statements)

References 27 publications

(35 reference statements)

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“…In the first part, the best color space, which is useful for the edge-detection process, is determined, and in the second part, the results of edge-preserving algorithms (that of Chung et al [8] and the proposed algorithm) in saturated CIE Lu'v' color space are compared. For comparing the results in both parts, 6 test images are used, which are shown in Figure 10.…”

Section: Resultsmentioning

confidence: 99%

“…This method contains 3 parts: image saturation, image desaturation, and a new edge-preserving algorithm proposed by Chung et al [8].…”

Section: Methods Of Chung Et Almentioning

confidence: 99%

“…Therefore, a desaturation process is needed. As can be seen in Figure 2b, other papers, such as [8], have determined the components of a desaturated pixel…”

Section: Image Desaturationmentioning

confidence: 99%

“…This paper is organized as follows: In Section 2, the CIE Lu'v' color space and Trahanias edge detector are introduced. Section 3 consists of 2 edge-preserving algorithms, Chung et al's [8] and our proposed algorithm. The experimental results are presented in Section 4 and, finally, some conclusions are addressed in Section 5.…”

Section: Introductionmentioning

confidence: 99%

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A new edge-preserving algorithm based on the CIE- Lu''v'' color space for color contrast enhancement

Zolfaghari¹,

Yazdi²

2014

Turk J Elec Eng & Comp Sci

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Image segmentation and edge detection are the most important presteps in machine vision, and their successfulness can affect the success of the next steps. In this paper, the performance of the Trahanias edge detector in different color spaces, such as RGB, YCbCr, HSI, and CIE Lu'v', is compared in order to find the best color space for image segmentation and edge detection. We then offer an efficient edge-preserving algorithm for color contrast enhancement in the CIE Lu'v' space. The proposed algorithm can increase the color contrast, which causes a remarkable improvement in image segmentation and edge detection in the CIE Lu'v' color space. Moreover, it can efficiently reduce the number of spurious edges that may be produced during the color contrast enhancement process. The results obtained by applying the proposed algorithm, as compared with those by applying another recently introduced algorithm, demonstrate the better performance of the proposed algorithm.

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Section: Resultsmentioning

confidence: 99%

“…This method contains 3 parts: image saturation, image desaturation, and a new edge-preserving algorithm proposed by Chung et al [8].…”

Section: Methods Of Chung Et Almentioning

confidence: 99%

“…Therefore, a desaturation process is needed. As can be seen in Figure 2b, other papers, such as [8], have determined the components of a desaturated pixel…”

Section: Image Desaturationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A new edge-preserving algorithm based on the CIE- Lu''v'' color space for color contrast enhancement

Zolfaghari¹,

Yazdi²

2014

Turk J Elec Eng & Comp Sci

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show abstract

“…Rawashdeh et al (2006) used remote sensing techniques in geological studies in El-Azraq area, Jordan. Chung et al (2008) proposed algorithm for color contrast enhancement.…”

Section: Introductionmentioning

confidence: 99%

Application of Digital Image Processing Techniques to Geological and Geomorphological Features of Southwest Jordan

Al-Shumaimri¹

2012

JGG

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A Landsat image of the multispectral scanner system covering an area lying between the Aqabah Gulf and the southern margin of the Dead Sea was analyzed by digital image processing techniques to delineate various geological and structural features of southwest Jordan area. Two major techniques in digital image processing were employed. They are preprocessing and enhancement, and their constituent treatment processes. Types of lithology, lineaments and topographic contrasts of southwest Jordan were used as test criteria. Results of comparison indicate that the combination of images processed by first principal component, second principal component and filtered first principal component as assigned to the hue, saturation and intensity system coordinates, respectively, provided better results than products of other digital techniques. Such good results enable geologists to map major lithologies, lineaments and other structural features effectively, as well as to assess topographic variations.

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Weld Microstructural Image Segmentation for Detection of Intermetallic Compounds Using Support Vector Machine Classification

Kumar¹,

Ramesh²,

Mohandas³

et al. 2021

Recent Advances in Manufacturing, Automation, Design and Energy Technologies

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Efficient edge-preserving algorithm for color contrast enhancement with application to color image segmentation

Cited by 20 publications

References 27 publications

A new edge-preserving algorithm based on the CIE- Lu''v'' color space for color contrast enhancement

A new edge-preserving algorithm based on the CIE- Lu''v'' color space for color contrast enhancement

Application of Digital Image Processing Techniques to Geological and Geomorphological Features of Southwest Jordan

Weld Microstructural Image Segmentation for Detection of Intermetallic Compounds Using Support Vector Machine Classification

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