Noise-aided dynamic range compression using selective processing in a statistics-dependent stochastic resonance model
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.
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.
References
More filters
TL;DR: Experimental results show that the proposed FDRCLCP algorithm not only provides good visual representation in both quantitative and visual comparisons, but also achieves real-time performance for video processing.
Abstract: This study addresses low dynamic range (LDR) image/video enhancement for digital video cameras. A new fast dynamic range compression format with a local-contrast-preservation (FDRCLCP) algorithm resolves this problem efficiently. The proposed FDRCLCP algorithm can combine with any continuously differentiable intensity transfer function to achieve LDR image enhancement. In combination with the FDRCLCP algorithm, a new intensity-transfer function is proposed, adaptively accomplishing dynamic range compression and edge-contrast enhancement depending on the local mean value of the input luminance image. The proposed method also extends to a linear color remapping approach, not only preserving the original image's color information, but also controlling color saturation of the resulting image. Moreover, a look-up-table (LUT) acceleration approach improves the processing speed of the proposed FDRCLCP algorithm in processing video signals, allowing real-time video enhancement processing. Experimental results show that the proposed method not only provides good visual representation in both quantitative and visual comparisons, but also achieves real-time performance for video processing.
41 citations
"Noise-aided dynamic range compressi..." refers background in this paper
...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]....
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TL;DR: A noise reduction method and an adaptive contrast enhancement for local tone mapping (TM) that compresses the luminance of high dynamic range (HDR) image and decomposes the compressed luminance into multi-scale subbands using the discrete wavelet transform.
Abstract: In this paper, we propose a noise reduction method and an adaptive contrast enhancement for local tone mapping (TM). The proposed local TM algorithm compresses the luminance of high dynamic range (HDR) image and decomposes the compressed luminance of HDR image into multi-scale subbands using the discrete wavelet transform. For noise reduction, the decomposed images are filtered using a bilateral filter and soft-thresholding. And then, the dynamic ranges of the filtered subbands are enhanced by considering local contrast using the modified luminance compression function. Finally, the color of the tone-mapped image is reproduced using an adaptive saturation control parameter. We generate the tone-mapped image using the proposed local TM. Computer simulation with noisy HDR images shows the effectiveness of the proposed local TM algorithm in terms of visual quality as well as the local contrast. It can be used in various displays with noise reduction and contrast enhancement.
34 citations
"Noise-aided dynamic range compressi..." refers background in this paper
...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]....
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01 Sep 2012
TL;DR: The proposed contrast enhancement technique using scaling of internal noise of a dark image in discrete cosine transform (DCT) domain adopts a local adaptive processing and significantly enhances the image contrast and color information while ascertaining good perceptual quality.
Abstract: A contrast enhancement technique using scaling of internal noise of a dark image in discrete cosine transform (DCT) domain has been proposed in this paper. The mechanism of enhancement is attributed to noise-induced transition of DCT coefficients from a poor state to an enhanced state. This transition is effected by the internal noise present due to lack of sufficient illumination and can be modeled by a general bistable system exhibiting dynamic stochastic resonance. The proposed technique adopts a local adaptive processing and significantly enhances the image contrast and color information while ascertaining good perceptual quality. When compared with the existing enhancement techniques such as adaptive histogram equalization, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, multi-contrast enhancement, multi-contrast enhancement with dynamic range compression, color enhancement by scaling, edge-preserving multi-scale decomposition and automatic controls of popular imaging tool, the proposed technique gives remarkable performance in terms of relative contrast enhancement, colorfulness and visual quality of enhanced image.
34 citations
"Noise-aided dynamic range compressi..." refers background 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....
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TL;DR: The proposed framework is able to enhance a wavelet-coded image computationally efficiently with high image quality and less noise or other artifacts and produces encouraging results both visually and numerically compared to some existing approaches.
Abstract: This paper presents computationally efficient framework for color image enhancement in the compressed wavelet domain. The proposed approach is capable of enhancing both global and local contrast and brightness as well as preserving color consistency. The framework does not require inverse transform for image enhancement since linear scale factors are directly applied to both scaling and wavelet coefficients in the compressed domain, which results in high computational efficiency. Also contaminated noise in the image can be efficiently reduced by introducing wavelet shrinkage terms adaptively in different scales. The proposed method is able to enhance a wavelet-coded image computationally efficiently with high image quality and less noise or other artifacts. The experimental results show that the proposed method produces encouraging results both visually and numerically compared to some existing approaches.
31 citations
"Noise-aided dynamic range compressi..." refers background in this paper
...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]....
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03 Apr 2012
TL;DR: In this paper, a nonlinear non-dynamic stochastic resonance-based technique has been proposed for enhancement of dark and low contrast images, where a low contrast image is treated as a sub-threshold signal and noise-enhanced signal processing is applied to improve its contrast.
Abstract: In this paper, a nonlinear non-dynamic stochastic resonance-based technique has been proposed for enhancement of dark and low contrast images. A low contrast image is treated as a subthreshold signal and noise-enhanced signal processing is applied to improve its contrast. The proposed technique uniquely utilizes addition of external noise to neutralize the effect of internal noise (due to insufficient illumination) of a low contrast image. Random noise is added repeatedly to an image and is successively hard-thresholded followed by overall averaging. By varying the noise intensities, noise induced resonance is obtained at a particular optimum noise intensity. Performance of the proposed technique has been investigated for four types of noise distributions - gaussian, uniform, poisson and gamma. Quantitative evaluation of their performances have been done in terms of contrast enhancement factor, color enhancement and perceptual quality measure. Comparison with other existing spatial domain techniques shows that the proposed technique gives remarkable enhancement while ascertaining good perceptual quality.
28 citations
"Noise-aided dynamic range compressi..." refers 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....
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