Correction of the overexposed region in digital color image

Lee, Dae-Hong; Yoon, Yeo-Jin; Cho, Min-Young; Ko, Sung-Jea

doi:10.1109/tce.2014.6851990

Cited by 19 publications

(14 citation statements)

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“… Brightness thresholding method In [ 8 , 9 ] pixels with high brightness values are identified as over-exposed. In [ 8 ], brightness thresholding is performed in the CIELAB color space.…”

Section: Limitations Of Conventional Oer Detection Methodsmentioning

confidence: 99%

“…If the brightness value L* of a pixel is larger than 98, where 0 ≤ L* ≤ 100, the pixel is over-exposed. In [ 9 ], if the Y value in a YUV color space is greater than or equal to 230, the pixel is detected as over-exposed. Over-exposed map based thresholding method In [ 10 ], the use of an over-exposed map is proposed to describe how much a particular pixel is affected by an over-exposure.…”

Section: Limitations Of Conventional Oer Detection Methodsmentioning

confidence: 99%

Section: Limitations Of Conventional Oer Detection Methodsmentioning

confidence: 99%

“…When we detect the region in which the L* values of the pixels are larger than 98 [ 8 ], a small region around the pure white and bright yellow colors is detected as an OER only in the case of V = 255, as shown in Figure 1b . In Figure 1c , pixels whose Y ≥ 230 are detected [ 9 ]. When V = 255, the detected OER includes yellow and cyan colors, which do not seem to be over-exposed.…”

Section: Limitations Of Conventional Oer Detection Methodsmentioning

confidence: 99%

“…Specifically, OER detection is performed by finding a region consisting of pixels with a high level of brightness and low chromaticity. For example, because pixels with high brightness levels tend to have low chromaticity as well, several previous methods adopt the use of simple brightness thresholding [ 7 – 9 ]. If the brightness value of a pixel is larger than a predefined threshold value, the pixel is identified as over-exposed.…”

Section: Introductionmentioning

confidence: 99%

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A New Human Perception-Based Over-Exposure Detection Method for Color Images

Yoon

Byun

Lee

et al. 2014

Sensors

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To correct an over-exposure within an image, the over-exposed region (OER) must first be detected. Detecting the OER accurately has a significant effect on the performance of the over-exposure correction. However, the results of conventional OER detection methods, which generally use the brightness and color information of each pixel, often deviate from the actual OER perceived by the human eye. To overcome this problem, in this paper, we propose a novel method for detecting the perceived OER more accurately. Based on the observation that recognizing the OER in an image is dependent on the saturation sensitivity of the human visual system (HVS), we detect the OER by thresholding the saturation value of each pixel. Here, a function of the proposed method, which is designed based on the results of a subjective evaluation on the saturation sensitivity of the HVS, adaptively determines the saturation threshold value using the color and the perceived brightness of each pixel. Experimental results demonstrate that the proposed method accurately detects the perceived OER, and furthermore, the over-exposure correction can be improved by adopting the proposed OER detection method.

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“… Brightness thresholding method In [ 8 , 9 ] pixels with high brightness values are identified as over-exposed. In [ 8 ], brightness thresholding is performed in the CIELAB color space.…”

Section: Limitations Of Conventional Oer Detection Methodsmentioning

confidence: 99%