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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Journal Article•DOI•

Enhancement of dark and low-contrast images using dynamic stochastic resonance

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Rajlaxmi Chouhan¹, Rajib Kumar Jha, Prabir Kumar Biswas¹•Institutions (1)

Indian Institute of Technology Kharagpur¹

06 Jun 2013-Iet Image Processing

TL;DR: The internal noise of an image has been utilised to produce a noise-induced transition of a dark image from a state of low contrast to that of high contrast.

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Abstract: In this study, a dynamic stochastic resonance (DSR)-based technique in spatial domain has been proposed for the enhancement of dark- and low-contrast images. Stochastic resonance (SR) is a phenomenon in which the performance of a system (low-contrast image) can be improved by addition of noise. However, in the proposed work, the internal noise of an image has been utilised to produce a noise-induced transition of a dark image from a state of low contrast to that of high contrast. DSR is applied in an iterative fashion by correlating the bistable system parameters of a double-well potential with the intensity values of a low-contrast image. Optimum output is ensured by adaptive computation of performance metrics - relative contrast enhancement factor ( F ), perceptual quality measures and colour enhancement factor. When compared with the existing enhancement techniques such as adaptive histogram equalisation, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, edge-preserving multi-scale decomposition and automatic controls of popular imaging tools, the proposed technique gives significant performance in terms of contrast and colour enhancement as well as perceptual quality. Comparison with a spatial domain SR-based technique has also been illustrated.

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88 citations

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

...In the context of image enhancement, noise-aided stochastic resonance-based algorithms have been found to display noteworthy performance, especially in contrast enhancement of dark images in spatial [11], [12], [13], frequency [14], [15], multiresolutional [16], [17] domains....
[...]
...While the iteration termination in [13] occurred at the maximum possible contrast enhancement with a constraint on acceptable perceptual quality, the same cannot be useful here for two reasons....
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...By differentiation of the SNR equation for dynamic stochastic resonance [13] w....
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...As iteration termination is taken care of through parameter tuning, the cost of region recombination (as in [19]) and computing performance metrics as in [13] specifically for iteration termination, is therefore avoided....
[...]
...The input statistics-dependent SR (ISSR) model of [13] performs suitably in various domains for contrast enhancement of dark images, but is unsuitable for dynamic range compression, or enhancement of dark regions of an image without overbrightening the bright regions....
[...]

Journal Article•DOI•

Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance

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Choonwoo Ryu¹, Seong G. Kong¹, Hakil Kim²•Institutions (2)

Temple University¹, Inha University²

01 Jan 2011-Pattern Recognition Letters

TL;DR: Experimental results show that Gaussian noise added to low-quality fingerprint images enables the extraction of useful features for biometric identification by adding noise to the original signal.

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Abstract: This paper presents a new approach to enhancing feature extraction for low-quality fingerprint images by adding noise to the original signal. Feature extraction often fails for low-quality fingerprint images obtained from excessively dry or wet fingers. In nonlinear signal processing systems, a moderate amount of noise can help amplify a faint signal while excessive amounts of noise can degrade the signal. Stochastic resonance (SR) refers to a phenomenon where an appropriate amount of noise added to the original signal can increase the signal-to-noise ratio. Experimental results show that Gaussian noise added to low-quality fingerprint images enables the extraction of useful features for biometric identification. SR was applied to 20 fingerprint images in the FVC2004 DB2 database that were rejected by a state-of-the-art fingerprint verification algorithm due to failures in feature extraction. SR enabled feature extraction from 10 out of 11 low-quality images with poor contrast. The remaining nine images were damaged fingerprints from which no meaningful features can be obtained. Improved feature extraction using SR decreases an equal error rate of fingerprint verification from 6.55% to 5.03%. The receiver operating characteristic curve shows that the genuine acceptance rates are improved for all false acceptance rates.

...read moreread less

69 citations

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

...The noiseenhanced algorithm of [12], [18] are based on the application of non-dynamic stochastic resonance that involves creation of noisy image frames, followed by thresholding and averaging....
[...]
...In the context of image enhancement, noise-aided stochastic resonance-based algorithms have been found to display noteworthy performance, especially in contrast enhancement of dark images in spatial [11], [12], [13], frequency [14], [15], multiresolutional [16], [17] domains....
[...]

Journal Article•DOI•

Noise-induced contrast enhancement using stochastic resonance on singular values

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Rajib Kumar Jha¹, Rajlaxmi Chouhan²•Institutions (2)

Indian Institutes of Information Technology¹, Indian Institutes of Technology²

01 Feb 2014-Signal, Image and Video Processing

TL;DR: The proposed DSR-SVD technique is found to give noteworthy better performance in terms of contrast enhancement factor, color enhancement factor and perceptual quality measure.

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Abstract: In this paper, a dynamic stochastic resonance (DSR)-based technique in singular value domain for contrast enhancement of dark images has been presented. The internal noise due to the lack of illumination is utilized using a DSR iterative process to obtain enhancement in contrast, colorfulness as well as perceptual quality. DSR is a phenomenon that has been strategically induced and exploited and has been found to give remarkable response when applied on the singular values of a dark low-contrast image. When an image is represented as a summation of image layers comprising of eigen vectors and values, the singular values denote luminance information of each such image layer. By application of DSR on the singular values using the analogy of a bistable double-well potential model, each of the singular values is scaled to produce an image with enhanced contrast as well as visual quality. When compared with performance of some existing spatial domain enhancement techniques, the proposed DSR-SVD technique is found to give noteworthy better performance in terms of contrast enhancement factor, color enhancement factor and perceptual quality measure.

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59 citations

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

...A brief description of the ISSR model [13], [21] is given below in the interest of reading continuity....
[...]

Journal Article•DOI•

Enhancement of ultrasound images using stochastic resonance-based wavelet transform.

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V. P. Subramanyam Rallabandi¹•Institutions (1)

National Brain Research Centre¹

01 Jun 2008-Computerized Medical Imaging and Graphics

TL;DR: A technique using stochastic resonance (SR)-based wavelet transform for the enhancement of unclear diagnostic ultrasound images that enhances the edges more clearly and can also optimally enhance an image even if the image noise level is considerable.

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Abstract: Ultrasound diagnostic imaging technique is used to visualize muscles and internal organs, their size, structures and possible pathologies or lesions. The limited soft tissue contrast of ultrasound may lead to problems in characterizing perivascular soft tissues. We develop a technique using stochastic resonance (SR)-based wavelet transform for the enhancement of unclear diagnostic ultrasound images. The proposed method enhances the edges more clearly. The advantages of this method are that it can simultaneously operate both as an enhancement process as well as a noise-reduction operation, and that the method can also optimally enhance an image even if the image noise level is considerable.

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58 citations

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

...Algorithms of [11], [14], [16] use the concept of dynamic stochastic resonance, where SR is induced by modelling the motion of a particle in a double-well system with externally-added noise, and choosing processing parameters experimentally following a specific relation....
[...]
...In the context of image enhancement, noise-aided stochastic resonance-based algorithms have been found to display noteworthy performance, especially in contrast enhancement of dark images in spatial [11], [12], [13], frequency [14], [15], multiresolutional [16], [17] domains....
[...]

Proceedings Article•DOI•

Image enhancement using stochastic resonance [sonar image processing applications]

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Qinghua Ye¹, Haining Huang¹, Chunhua Zhang¹•Institutions (1)

Chinese Academy of Sciences¹

24 Oct 2004

TL;DR: The results show that the proposed method is suitable for noisy images with very low signal-to-noise ratio (SNR), when the texture of the object is not subtle, and the region where the object lies in is not too small compared to the minimal region coverage over which SR works.

...read moreread less

Abstract: This paper presents an image enhancement method using stochastic resonance (SR) and provides two applications to sonar image processing., i.e. side-scan sonar image and bearing-time record. Simulated and real data are tested and the results show that the proposed method is suitable for noisy images with very low signal-to-noise ratio (SNR), when the texture of the object is not subtle, and the region where the object lies in is not too small compared to the minimal region coverage over which SR works. We also show that an additional amount of noise besides the noise of the image itself may be helpful in enhancing the image.

...read moreread less

43 citations

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

...Algorithms of [11], [14], [16] use the concept of dynamic stochastic resonance, where SR is induced by modelling the motion of a particle in a double-well system with externally-added noise, and choosing processing parameters experimentally following a specific relation....
[...]
...In the context of image enhancement, noise-aided stochastic resonance-based algorithms have been found to display noteworthy performance, especially in contrast enhancement of dark images in spatial [11], [12], [13], frequency [14], [15], multiresolutional [16], [17] domains....
[...]

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 background or methods in this paper

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

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

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

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