High Dynamic Range image tone mapping based on local Histogram Equalization

Boschetti, Alberto; Adami, Nicola; Leonardi, Riccardo; Okuda, Masahiro

doi:10.1109/icme.2010.5583305

Cited by 26 publications

(21 citation statements)

References 10 publications

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“…When applying this index to a multiband image, it is applied bandby-band and averaged over all bands. [7]. …”

Section: Performance Parametersmentioning

confidence: 99%

“…The fusion [11] is done by region-enriched pseudo-exposures into an HDR image. Boschetti et al [7] worked on the tone map procedure, derived through Contrast Limited Adaptive Histogram Equalization (CLAHE) method. The comparison of obtained LDR images, with those obtained by State of the Art TMOs, has the ability to equally enhance visibility in both dark and bright areas.…”

Section: Introductionmentioning

confidence: 99%

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CIELAB based Tone-Mapping Algorithm for LDR Image Generation

Patle¹,

Jain²

2016

IJCA

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This paper presents a analysis of the CIELAB color feature based tone mapping technique. The basic tone mapping was generally the reverse going to the old technology objects compatibility. The compatibility is the basic requirement of the market to grow with the latest technology and the old objects to work with new technology. The paper worked for maintaining this compatibility. The basic theme of the work is done in the SCIELAB color space. The proposed method has done the tone mapping through the decomposition of the image in this SCIELAB color space. The Visual quality of the proposed method is same as of saliency based tone mapping but it is more computational efficient.

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“…When applying this index to a multiband image, it is applied bandby-band and averaged over all bands. [7]. …”

Section: Performance Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CIELAB based Tone-Mapping Algorithm for LDR Image Generation

Patle¹,

Jain²

2016

IJCA

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“…The first is to make the transformation function of histogram equalization more adaptive to local image signals. It can be done by modulating the "local" cumulative functions [2] or by adaptive clipping [3]. The other approach is to use low-pass filters to remove the noise generated by a histogram equalization process.…”

Section: Introductionmentioning

confidence: 99%

Pixel classification algorithms for noise removal and signal preservation in low-pass filtering for contrast enhancement

Wang

Gong

2014

2014 19th International Conference on Digital Signal Processing

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With a view to obtaining a high quality contrast enhancement, low-pass filters are used to remove the noise generated in a high-gain histogram equalization process. To preserve signal variations, the LP operation applied to the pixels in non-homogeneous regions should have less smoothing strength than that in homogeneous regions. The pixel classification according to the gray level homogeneity is thus a critical part in the LP filtering. In this paper, two algorithms for pixel classification according to the gray level homogeneity of their regions are proposed. In each of them, image pixels are grouped in such a way that, in the same group, pixels in homogeneous regions can be easily distinguished from those in nonhomogeneous regions by a simple gradient thresholding, despite the complexity of signal gradient degradation in images. The two proposed classification algorithms are very simple, requiring very small quantity of computation. Their effectiveness has been proven by the simulation results.

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“…I.R. Khan et al [23] and A. Boschetti et al [24] improved the histogram based algorithms by incorporating human visual system, and adjusting the histogram locally. Jiang Duan et al [25] neatly combined the global tone mapping operator HALEQ into local tone mapping operator ALHA, with fixed parameter values and good performance.…”

Section: High Dynamic Range Image Compression With Joint Adaptive Quamentioning

confidence: 99%

Adaptive quantization using piecewise companding and scaling for Gaussian mixture

Lei

2012

Journal of Visual Communication and Image Representation

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High Dynamic Range image tone mapping based on local Histogram Equalization

Cited by 26 publications

References 10 publications

CIELAB based Tone-Mapping Algorithm for LDR Image Generation

CIELAB based Tone-Mapping Algorithm for LDR Image Generation

Pixel classification algorithms for noise removal and signal preservation in low-pass filtering for contrast enhancement

Adaptive quantization using piecewise companding and scaling for Gaussian mixture

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