Fast and robust wavelet-based dynamic range compression with local contrast enhancement

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

doi:10.1117/12.778025

Cited by 12 publications

(11 citation statements)

References 17 publications

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“…The quantitative method presented in [23], which had been used in previous studies [12,15,24], is employed in the experiments to quantitatively evaluate the performance of the proposed method and three state-of-the-art methods: MSR [14], adaptive and integrated neighborhooddependent approach for nonlinear enhancement (AIN-DANE) [12], and WDRC [18]. Table 1 tabulates the parameter setting for each compared method used in the experiments.…”

Section: Quantitative Comparison With Other Methodsmentioning

confidence: 99%

“…Although the linear RGB color remapping method (18) provides an efficient way to preserve the color information of the input color, YC b C r is the most commonly used color space to render video stream in digital video standards. Most video enhancement methods are processing in YC b C r color space; however, they usually result with less saturated colors due to only enhancing Y component while leaving C b , C r components unchanged.…”

Section: Linear Remapping In Yc B C R Color Spacementioning

confidence: 99%

“…This requirement takes high computational costs with a large memory and leads to an inefficient algorithm. Recently, Unaldi et al [18] proposed a fast and robust wavelet-based dynamic range compression (WDRC) algorithm with local contrast enhancement. The authors also extended WDRC algorithm to combine with a linear color restoration process to cope with color constancy problem [19].…”

Section: Introductionmentioning

confidence: 99%

“…(3) The proposed adaptive intensity transfer function is a spatially variant mapping function associated with the local statistical characteristics of the image. Therefore, unlike wavelet-based approaches [18,19], the proposed method is able to produce satisfactory contrast enhancement for preserving visual details of LDR images. (4) By combining the proposed adaptive intensity transfer function with SDRCLCE algorithm, the proposed method possesses the adjustability to separately control the level of dynamic range compression and local contrast enhancement.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A novel simultaneous dynamic range compression and local contrast enhancement algorithm for digital video cameras

Tsai

Chou

2011

J Image Video Proc.

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This article addresses the problem of low dynamic range image enhancement for commercial digital cameras. A novel simultaneous dynamic range compression and local contrast enhancement algorithm (SDRCLCE) is presented to resolve this problem in a single-stage procedure. The proposed SDRCLCE algorithm is able to combine with many existent intensity transfer functions, which greatly increases the applicability of the proposed method. An adaptive intensity transfer function is also proposed to combine with SDRCLCE algorithm that provides the capability to adjustably control the level of overall lightness and contrast achieved at the enhanced output. Moreover, the proposed method is amenable to parallel processing implementation that allows us to improve the processing speed of SDRCLCE algorithm. Experimental results show that the performance of the proposed method outperforms three state-of-the-art methods in terms of dynamic range compression and local contrast enhancement.Keywords: low dynamic range image enhancement, dynamic range compression, local contrast enhancement, statistics of visual representation, quantitative evaluation.

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Section: Quantitative Comparison With Other Methodsmentioning

confidence: 99%

Section: Linear Remapping In Yc B C R Color Spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel simultaneous dynamic range compression and local contrast enhancement algorithm for digital video cameras

Tsai

Chou

2011

J Image Video Proc.

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“…This method usually performs well in color image enhancement; however, its enhancement procedure requires high computational costs with a large memory and leads to an inefficient algorithm. To improve computational efficiency, Unaldi et al proposed a fast and robust wavelet-based dynamic range compression (WDRC) algorithm with localcontrast enhancement [12]. The processing time of WDRC algorithm is notably reduced, since it fully operates in wavelet domain.…”

mentioning

confidence: 98%

A GPU-Accelerated Adaptive Simultaneous Dynamic Range Compression and Local Contrast Enhancement Algorithm for Real-Time Color Image Enhancement

Tsai

2015

Color Image and Video Enhancement

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Modern robotic vision systems usually require the use of image enhancement algorithms as they play an important preliminary processing role in computer vision applications. Numerous image enhancement methods have been proposed to deal with monochromatic images. However, they often cannot be directly applied on multichannel images, which usually give more information about the environment than monochromatic images. Consequently, color image enhancement has now become an active research issue in image enhancement processing. Moreover, because color images contain much more data to be processed, the improvement on computational efficiency of color image enhancement to achieve real-time performance is still a challenging task.This chapter presents a parallel implementation of an existing adaptive color image enhancement scheme, which improves visual quality of color images suffered from low dynamic range (LDR) and poor contrast defects. Images captured from a digital camera may be in poor visibility due to the limitation on dynamic range of image sensors. This problem typically can be resolved by compressing the dynamic range of captured images, and this image enhancement process is commonly known as dynamic range compression. Several dynamic range compression techniques have been proposed based on Retinex theory, which is a lightness and color perception model of human vision [1]. Retinex-based techniques [2][3][4][5][6][7] are general purpose methods, simultaneously achieving dynamic range compression, local-contrast enhancement, and color consistency; however, these algorithms are usually computationally expensive, requiring algorithmic simplification and hardware acceleration to achieve real-time performance [8].

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An adaptive dynamic range compression with local contrast enhancement algorithm for real-time color image enhancement

Tsai

2012

J Real-Time Image Proc

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Fast and robust wavelet-based dynamic range compression with local contrast enhancement

Cited by 12 publications

References 17 publications

A novel simultaneous dynamic range compression and local contrast enhancement algorithm for digital video cameras

A novel simultaneous dynamic range compression and local contrast enhancement algorithm for digital video cameras

A GPU-Accelerated Adaptive Simultaneous Dynamic Range Compression and Local Contrast Enhancement Algorithm for Real-Time Color Image Enhancement

An adaptive dynamic range compression with local contrast enhancement algorithm for real-time color image enhancement

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