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Proceedings ArticleDOI

Image enhancement and dynamic range compression using novel intensity-specific stochastic resonance-based parametric image enhancement model

TL;DR: A noise-aided image enhancement algorithm focussed on addressing images that have a large dynamic range, i.e., images with both dark and bright regions, and the application of a new mathematical model, in a shifted double-well system exhibiting stochastic resonance, is investigated.
Abstract: This paper presents a noise-aided image enhancement algorithm focussed on addressing images that have a large dynamic range, i.e., images with both dark and bright regions. The application of a new mathematical model, in a shifted double-well system exhibiting stochastic resonance, is investigated for such images. The new mathematical model addresses the shortcomings of earlier SR-based enhancement model by deriving parameters purely from input values (instead of input statistics). This model is specific to spatial domain pixel representation and operates on a revised iterative equation. This iterative processing is here applied selectively to the under-illuminated regions of the image, characterized as the De Vries-Rose (DVR) region of a human psychovisual model. The idea of suitably modifying the existing universal image quality index is also proposed for its participation in iteration termination, and to gauge the property of dynamic range compression. While the iterative algorithm is terminated using the revised image quality index, entropy maximization, and contrast quality of DVR region with constraints on perceptual quality, the performance of the proposed algorithm is also characterized by observing color enhancement and subjective scores on visual quality.
Citations
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Journal ArticleDOI
TL;DR: The proposed noise-enhanced iterative processing on Fourier coefficients for enhancement of low-contrast images has been found to give noteworthy performance for both low- Contrast and dark images among the SR-based techniques and is found to be better than most of the non-SR- based techniques, in terms of contrast enhancement, perceptual quality and colorfulness.
Abstract: This paper presents a study of noise-enhanced iterative processing on Fourier coefficients for enhancement of low-contrast images. The processing equation is derived from the concept of dynamic stochastic resonance (SR), where the presence of optimum amount of noise produces an improved performance in the system. Similar to our earlier works on SR-based contrast enhancement, noise in the current context is the internal noise inherent in an image due to insufficient illumination. Here, however, the parameter selection is done so as to achieve large noise suppression. Iteration is terminated when target performance has been achieved. It is observed that the increase in the variance of the Fourier magnitude distribution leads to an increase in the contrast of the image. The increase in the variance is analytically proven to be equivalent to the process of coefficient rooting. Comparison has been made with various state-of-the-art SR and non-SR-based techniques in spatial/frequency domains. The proposed technique has been found to give noteworthy performance for both low-contrast and dark images among the SR-based techniques. The performance is also found to be better than most of the non-SR-based techniques, in terms of contrast enhancement, perceptual quality and colorfulness.

12 citations

Journal ArticleDOI
TL;DR: It can be inferred from comparative analysis with respect to other conventional methods that while the algorithm is observed to work well in all three hybrid domains, the SV-DCT domain performs better in terms of iteration count, while DCT-DWT is found to outperform others in Terms of perceptual quality.
Abstract: This paper aims to present an analysis of a noise-aided contrast enhancement algorithm in hybrid transform domains. The performance of our earlier noise-enhanced iterative algorithm, formulated from the motion dynamics of a double-well system exhibiting dynamic stochastic resonance, has been investigated here on hybrid coefficients, viz. singular values (SVs) of wavelet coefficients, SVs of discrete cosine transform (DCT) coefficients, and DCT of wavelet coefficients, of a dark image. The performance of the algorithm is gauged using metrics indicating relative contrast enhancement and perceptual quality. Colorfulness, subjective visual scores and logarithmic contrast metrics for outputs are also observed. Experimental results display noteworthy enhancement of contrast on both natural and synthetically-darkened images. It can be inferred from comparative analysis with respect to other conventional methods that while the algorithm is observed to work well in all three hybrid domains, the SV-DCT domain performs better in terms of iteration count, while DCT-DWT is found to outperform others in terms of perceptual quality.

4 citations

Dissertation
01 Jan 2016
TL;DR: Li et al. as discussed by the authors proposed a new model for real-time tracking of the human body based on the MFBM model, which can detect movimiento in camaras no estaticas.
Abstract: La videovigilancia por medios automaticos es un campo de investigacion muy activo debido a la necesidad de seguridad y control. En este sentido, existen situaciones que dificultan el correcto funcionamiento de los algoritmos ya existentes. Esta tesis se centra en la deteccion de movimiento y aborda varias de las problematicas habituales, planteando nuevos enfoques que, en la gran mayoria de las ocasiones, superan a otras propuestas pertenecientes al estado del arte. En particular estudiamos: - La importancia del espacio de color de cara a la deteccion de movimiento. - Los efectos del ruido en el video de entrada. - Un nuevo modelo de fondo denominado MFBM que acepta cualquier numero y tipo de rasgo de entrada. - Un metodo para paliar las dificultades que suponen los cambios de iluminacion. - Un metodo no panoramico para detectar movimiento en camaras no estaticas. Durante la tesis se han utilizado diferentes repositorios publicos que son ampliamente utilizados en el ambito de la deteccion de movimiento. Ademas, los resultados obtenidos han sido comparados con los de otras propuestas existentes. Todo el codigo utilizado ha sido colgado en la Web de forma publica. En esta tesis se llega a las siguientes conclusiones: - El espacio de color con el que se codifique el video de entrada repercute notablemente en el rendimiento de los metodos de deteccion. El modelo RGB no siempre es la mejor opcion. Tambien se ha comprobado que ponderar los canales de color del video de entrada mejora el rendimiento de los metodos. - El ruido en el video de entrada a la hora de realizar la deteccion de movimiento es un factor a tener en cuenta ya que condiciona el rendimiento de los metodos. Resulta llamativo que, si bien el ruido suele ser perjudicial, en ocasiones puede mejorar la deteccion. - El modelo MFBM supera a los demas metodos competidores estudiados, todos ellos pertenecientes al estado del arte. - Los problemas derivados de los cambios de iluminacion se reducen significativamente al utilizar el metodo propuesto. - El metodo propuesto para detectar movimiento con camaras no estaticas supera en la gran mayoria de las ocasiones a otras propuestas existentes. Se han consultado 280 entradas bibliograficas, entre ellas podemos destacar: - C. Wren, A. Azarbayejani, T. Darrell, and A. Pentl, “Pfinder: real-time tracking of the human body,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, pp. 780–785, 1997. - C. Stauffer and W. Grimson, “Adaptive background mixture models for real-time tracking,” in Proc. IEEE Intl. Conf. on Computer Vision and Pattern Recognition, 1999. - L. Li, W. Huang, I.-H. Gu, and Q. Tian, “Statistical modeling of complex backgrounds for foreground object detection,” Image Processing, IEEE Transactions on, vol. 13, pp. 1459–1472, 2004. - T. Bouwmans, “Traditional and recent approaches in background modeling for foreground detection: An overview,” Computer Science Review, vol. 11-12, pp. 31 – 66, 2014.

2 citations


Cites background from "Image enhancement and dynamic range..."

  • ...Esto tiene múltiples aplicaciones, entre ellas la mejora de imágenes [180, 181]....

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Journal ArticleDOI
TL;DR: A high-contrast, edge-preserved and brightness-improved image is obtained by the processing steps considered in this work to get good visual quality.
Abstract: Integrating complementary information with high-quality visual perception is essential in infrared and visible image fusion. Contrast-enhanced fusion required for target detection in military, navigation and surveillance applications, where visible images are captured at low-light conditions, is a challenging task. This paper aims to focus on the enhancement of poorly illuminated low-light images through decomposition prior to fusion, to provide high visual quality.,In this paper, a two-step process is implemented to improve the visual quality. First, the low-light visible image is decomposed to dark and bright image components. The decomposition is accomplished based on the selection of a threshold using Renyi’s entropy maximization. The decomposed dark and bright images are intensified with the stochastic resonance (SR) model. Second, texture information-based weighted average scheme for low-frequency coefficients and select maximum precept for high-frequency coefficients are used in the discrete wavelet transform (DWT) domain.,Simulations in MATLAB were carried out on various test images. The qualitative and quantitative evaluations of the proposed method show improvement in edge-based and information-based metrics compared to several existing fusion techniques.,In this work, a high-contrast, edge-preserved and brightness-improved image is obtained by the processing steps considered in this work to get good visual quality.

1 citations

Proceedings ArticleDOI
01 Dec 2015
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.
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.

Cites background or methods from "Image enhancement and dynamic range..."

  • ...Among those listed, Selective-IVSR [19] is the only iterative dynamic SR-based algorithm that produces DRC, and gives best TMQI but at the cost of larger t0....

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  • ...More recently, a noise-aided dynamic range compression algorithm [19] was reported using intensity-specific value-dependent SR (IVSR model) parameter selection and selective-processing of psychovisually underexposed regions....

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  • ...Input Selective-ISSR (Proposed) Selective-IVSR [19] AHE MSR [1]...

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  • ...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....

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  • ...It is found that while Selective-IVSR takes nine iterations for all test images (owing to the mapping characteristics of the IVSR model), the optimal iteration count for the same test images using proposed method was lesser, despite the use of semi-adaptively decreasing value of Δt....

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References
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Journal ArticleDOI
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Abstract: Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

40,609 citations

Journal ArticleDOI
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Abstract: We propose a new universal objective image quality index, which is easy to calculate and applicable to various image processing applications. Instead of using traditional error summation methods, the proposed index is designed by modeling any image distortion as a combination of three factors: loss of correlation, luminance distortion, and contrast distortion. Although the new index is mathematically defined and no human visual system model is explicitly employed, our experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error. Demonstrative images and an efficient MATLAB implementation of the algorithm are available online at http://anchovy.ece.utexas.edu//spl sim/zwang/research/quality_index/demo.html.

5,285 citations


"Image enhancement and dynamic range..." refers methods in this paper

  • ...This selected region is processed for enhancement as described in the following sections....

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Journal ArticleDOI
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.
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.

2,395 citations


"Image enhancement and dynamic range..." refers background or methods in this paper

  • ...Index Terms— Image enhancement, double-well model, stochastic resonance, dynamic range compression, HVS, image quality...

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  • ...This iterative process is terminated using the criteria discussed as follows....

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Journal ArticleDOI
TL;DR: A practical implementation of the retinex is defined without particular concern for its validity as a model for human lightness and color perception, and the trade-off between rendition and dynamic range compression that is governed by the surround space constant is described.
Abstract: The last version of Land's (1986) retinex model for human vision's lightness and color constancy has been implemented and tested in image processing experiments. Previous research has established the mathematical foundations of Land's retinex but has not subjected his lightness theory to extensive image processing experiments. We have sought to define a practical implementation of the retinex without particular concern for its validity as a model for human lightness and color perception. We describe the trade-off between rendition and dynamic range compression that is governed by the surround space constant. Further, unlike previous results, we find that the placement of the logarithmic function is important and produces best results when placed after the surround formation. Also unlike previous results, we find the best rendition for a "canonical" gain/offset applied after the retinex operation. Various functional forms for the retinex surround are evaluated, and a Gaussian form is found to perform better than the inverse square suggested by Land. Images that violate the gray world assumptions (implicit to this retinex) are investigated to provide insight into cases where this retinex fails to produce a good rendition.

1,674 citations


"Image enhancement and dynamic range..." refers background in this paper

  • ...Index Terms— Image enhancement, double-well model, stochastic resonance, dynamic range compression, HVS, image quality...

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Proceedings ArticleDOI
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.
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.

913 citations


"Image enhancement and dynamic range..." refers methods in this paper

  • ...This selected region is processed for enhancement as described in the following sections....

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