Noise-aided dynamic range compression using selective processing in a statistics-dependent stochastic resonance model

doi:10.1109/VCIP.2015.7457836

Proceedings Article•DOI•

Noise-aided dynamic range compression using selective processing in a statistics-dependent stochastic resonance model

Rajlaxmi Chouhan¹, Prabir Kumar Biswas¹•Institutions (1)

Indian Institute of Technology Kharagpur¹

01 Dec 2015-pp 1-4

TL;DR: It is observed that by semi-adaptively changing the processing parameters with iteration, the processed dark regions and the unprocessed bright regions of an image smoothly merge producing a quality of dynamic range compression in the image.

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Abstract: This paper presents a noise-aided dynamic range compression algorithm using a stochastic resonance model in spatial domain. An input statistics-dependent stochastic resonance (ISSR) model, that is designed for contrast enhancement of dark images, is used here to enhance an image with both bright and dark areas. The underilluminated regions of such an image are selected as the De Vries Rose region from a human visual system-based segmentation algorithm, and then processed using the ISSR model. It is observed that by semi-adaptively changing the processing parameters with iteration, the processed dark regions and the unprocessed bright regions of an image smoothly merge producing a quality of dynamic range compression in the image. The performance of the proposed algorithm is characterized using image quality index for tone-mapped images and a no-reference perceptual quality measure. Results and comparative analysis suggest notable performance of the proposed algorithm with fewer iteration.

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Stochastic Resonance

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Mark D. McDonnell, Derek Abbott, Nigel G. Stocks, Charles E. M. Pearce

01 Jan 2008

TL;DR: In this article, a theoretical approach based on linear response theory (LRT) is described, and two new forms of stochastic resonance, predicted on the basis of LRT and subsequently observed in analogue electronic experiments, are described.

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Abstract: Stochastic resonance (SR) - a counter-intuitive phenomenon in which the signal due to a weak periodic force in a nonlinear system can be {\it enhanced} by the addition of external noise - is reviewed A theoretical approach based on linear response theory (LRT) is described It is pointed out that, although the LRT theory of SR is by definition restricted to the small signal limit, it possesses substantial advantages in terms of simplicity, generality and predictive power The application of LRT to overdamped motion in a bistable potential, the most commonly studied form of SR, is outlined Two new forms of SR, predicted on the basis of LRT and subsequently observed in analogue electronic experiments, are described

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2,403 citations

Journal Article•DOI•

A multiscale retinex for bridging the gap between color images and the human observation of scenes

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D.J. Jobson¹, Zia-ur Rahman², G.A. Woodell¹•Institutions (2)

Langley Research Center¹, College of William & Mary²

01 Jul 1997-IEEE Transactions on Image Processing

TL;DR: This paper extends a previously designed single-scale center/surround retinex to a multiscale version that achieves simultaneous dynamic range compression/color consistency/lightness rendition and defines a method of color restoration that corrects for this deficiency at the cost of a modest dilution in color consistency.

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Abstract: Direct observation and recorded color images of the same scenes are often strikingly different because human visual perception computes the conscious representation with vivid color and detail in shadows, and with resistance to spectral shifts in the scene illuminant. A computation for color images that approaches fidelity to scene observation must combine dynamic range compression, color consistency-a computational analog for human vision color constancy-and color and lightness tonal rendition. In this paper, we extend a previously designed single-scale center/surround retinex to a multiscale version that achieves simultaneous dynamic range compression/color consistency/lightness rendition. This extension fails to produce good color rendition for a class of images that contain violations of the gray-world assumption implicit to the theoretical foundation of the retinex. Therefore, we define a method of color restoration that corrects for this deficiency at the cost of a modest dilution in color consistency. Extensive testing of the multiscale retinex with color restoration on several test scenes and over a hundred images did not reveal any pathological behaviour.

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2,395 citations

"Noise-aided dynamic range compressi..." refers background or methods in this paper

...Input Selective-ISSR (Proposed) Selective-IVSR [19] AHE MSR [1]...
[...]
...CVC gives the best visual output, while AHE and MSR also perform well but produce somewhat noisy outputs....
[...]
...5, and the quantitative performance values in terms of TMQI, PQM, and iteration count, t0, are displayed in Table I. Visually, the proposed method gives noteworthy and comparable performance with Selective-IVSR, MSR, HMF, and better outputs than PS-AC and MCEDRC....
[...]
...As dynamic range compression (DRC) is obtained in the proposed selective-ISSR algorithm, we present a comparison with some algorithms that produce a DRC quality, such as, selective-IVSR [19], classical adaptive histogram equalization (AHE), multiscale retinex (MSR) [1], homomorphic filtering (HMF), multicontrast enhancement with DRC (MCEDRC) [2], scaling of DCT coefficients with suppression of blocking artifacts (DRC-CES-BLK) [3], Auto Contrast of Adobe Photoshop (PS-AC), and contextual and variational contrast enhancement (CVC) [4]....
[...]
...Several remarkable enhancement and dynamic range compression algorithms, in spatial and frequency domains, have been found in the literature in the past several years [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]....
[...]

Proceedings Article•DOI•

No-reference perceptual quality assessment of JPEG compressed images

[...]

Zhou Wang, Hamid R. Sheikh, Alan C. Bovik

10 Dec 2002

TL;DR: It is shown that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality and tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics.

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Abstract: Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available. This research aims to develop NR quality measurement algorithms for JPEG compressed images. First, we established a JPEG image database and subjective experiments were conducted on the database. We show that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality. Therefore, tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics. Furthermore, we propose a computational and memory efficient NR quality assessment model for JPEG images. Subjective test results are used to train the model, which achieves good quality prediction performance.

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913 citations

"Noise-aided dynamic range compressi..." refers methods in this paper

...In order to gauge the individual perceptual quality, we also use a no-reference perceptual quality metric (PQM ) [24] that takes into account the blockiness and blurriness....
[...]

Journal Article•DOI•

Objective Quality Assessment of Tone-Mapped Images

[...]

Hojatollah Yeganeh¹, Zhou Wang¹•Institutions (1)

University of Waterloo¹

01 Feb 2013-IEEE Transactions on Image Processing

TL;DR: An objective quality assessment algorithm for tone-mapped images is proposed by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure onThe basis of intensity statistics of natural images.

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Abstract: Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.

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525 citations

"Noise-aided dynamic range compressi..." refers methods in this paper

...A state-of-theart objective measure for assessing image quality of tone-mapped images (TMQI) as reported in [23] has been used here....
[...]

Journal Article•DOI•

Contextual and Variational Contrast Enhancement

[...]

Turgay Celik¹, Tardi Tjahjadi¹•Institutions (1)

University of Warwick¹

01 Dec 2011-IEEE Transactions on Image Processing

TL;DR: An algorithm that enhances the contrast of an input image using interpixel contextual information and produces better or comparable enhanced images than four state-of-the-art algorithms is proposed.

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Abstract: This paper proposes an algorithm that enhances the contrast of an input image using interpixel contextual information. The algorithm uses a 2-D histogram of the input image constructed using a mutual relationship between each pixel and its neighboring pixels. A smooth 2-D target histogram is obtained by minimizing the sum of Frobenius norms of the differences from the input histogram and the uniformly distributed histogram. The enhancement is achieved by mapping the diagonal elements of the input histogram to the diagonal elements of the target histogram. Experimental results show that the algorithm produces better or comparable enhanced images than four state-of-the-art algorithms.

...read moreread less

383 citations

"Noise-aided dynamic range compressi..." refers background or methods in this paper

...CVC gives the best visual output, while AHE and MSR also perform well but produce somewhat noisy outputs....
[...]
...As dynamic range compression (DRC) is obtained in the proposed selective-ISSR algorithm, we present a comparison with some algorithms that produce a DRC quality, such as, selective-IVSR [19], classical adaptive histogram equalization (AHE), multiscale retinex (MSR) [1], homomorphic filtering (HMF), multicontrast enhancement with DRC (MCEDRC) [2], scaling of DCT coefficients with suppression of blocking artifacts (DRC-CES-BLK) [3], Auto Contrast of Adobe Photoshop (PS-AC), and contextual and variational contrast enhancement (CVC) [4]....
[...]
...HMF MCEDRC [2] DRC-CES-BLK [3] PS-AC CVC [4]...
[...]
...Several remarkable enhancement and dynamic range compression algorithms, in spatial and frequency domains, have been found in the literature in the past several years [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]....
[...]

Noise-aided dynamic range compression using selective processing in a statistics-dependent stochastic resonance model

References

"Noise-aided dynamic range compressi..." refers background or methods in this paper

"Noise-aided dynamic range compressi..." refers methods in this paper

"Noise-aided dynamic range compressi..." refers methods in this paper

"Noise-aided dynamic range compressi..." refers background or methods in this paper

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