A Specular Removal Algorithm Based on Improved Specular-free Image and Chromaticity Analysis

Xu, Qian; Zhou, Liang

doi:10.1109/cisp-bmei51763.2020.9263590

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…Many single-image methods start with pseudo specular reflection and iteratively solve the inverse problem using optimization techniques. Xu and Zhou [11] and Xia et al [13] obtain a pseudo specular reflection by thresholding input pixels with the Value in the HSV color space. Kim et al [15] and Ramos et al [16] proposed that the minimum intensity among the RGB channels for each pixel can be used as a prior of specular reflection.…”

Section: A a Single-image Approachmentioning

confidence: 99%

“…To find a saturated pixel, previous studies [11], [12], [13], [14] threshold the intensity of a pixel, while the proposed method imposes an additional temporal constraint on it. Under AC light sources, the intensity in the non-saturated regions is sinusoidally varying with time, but the intensity in the saturated region is constant.…”

Section: B Loss Functionsmentioning

confidence: 99%

“…Several previous studies on highlight removal have used a prior for specular reflection. To determine pseudo specular reflection, they studied a threshold for Value or intensity [11], [12], [13], [14] and used the minimum of RGB channels [15], [16]. In this paper, a new prior for the diffuse component is proposed for stable convergence and accurate model estimation.…”

Section: Introductionmentioning

confidence: 99%

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Deep Highlight Removal Using Temporal Dark Prior in High-Speed Domain

Lee

Yoo

et al. 2023

IEEE Access

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This paper proposes a deep highlight removal method based on the dichromatic model under alternating current (AC) light sources with a new diffuse prior on temporal domain, temporal dark prior. An input image is decomposed into specular and diffuse components using a deep network. Due to AC powered lights, both incident and reflected lights are time-varying. We exploit the periodic variation property of the specular and diffuse reflections as a prior for dichromatic model based image decomposition. In addition, we propose a new temporal dark prior as a pseudo-diffuse reflection. Unlike the conventional prior in the spatial domain, to the best of our knowledge, this is the first study to utilize a diffuse prior on the temporal domain for highlight removal. The blurred version of the temporal dark prior is additionally fed to the network to alleviate hole artifacts. It is demonstrated through diverse experiments that these temporal priors can strongly contribute to accurate image decomposition, leading to better highlight removal. INDEX TERMS Dichromatic model, highlight removal, high-speed camera.The associate editor coordinating the review of this manuscript and approving it for publication was Yongjie Li.

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Section: A a Single-image Approachmentioning

confidence: 99%

Section: B Loss Functionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep Highlight Removal Using Temporal Dark Prior in High-Speed Domain

Lee

Yoo

et al. 2023

IEEE Access

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“…Dichromatic model based decomposition separates diffuse and specular reflection from an input image, and due to its ill-posed property, various priors have been investigated. The thresholded Value in the HSV color space [40], [41] and minimum intensity among the RGB channels for each pixel [42], [43] were explored as the prior of specular reflection. Several methods use color dictionary to recover the chromaticity of diffuse reflection, based on the assumption that diffuse color can be expressed as a linear combination of some representative colors [44], [45], [46].…”

Section: B Dichromatic Model Based Decompositionmentioning

confidence: 99%

Joint Deep Estimation of Intrinsic and Dichromatic Image Decomposition

Lee

Kim

2023

IEEE Access

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This paper proposes an image formation model that jointly combines dichromatic and intrinsic image decomposition models. The two decomposition models analyze image formation process from a different perspective, and they can be combined synergistically. It is confirmed that the proposed method performs better than the individual decomposition. The joint estimation and the study of the decomposition order ('intrinsic + dichromatic' or 'dichromatic + intrinsic') are the first attempt to the best of our knowledge. It was confirmed that the proposed 'intrinsic + dichromatic' is more optimal through experimental evaluations. We also exploit the temporal property of AC light sources, which can further improve the decomposition performance. The experimental results show that the proposed model can make an accurate image decomposition and achieve a remarkable color constancy performance.INDEX TERMS Intrinsic image decomposition, dichromatic model, color constancy, AC light, high-speed video.

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“…Klinker et al separated the diffuse reflection from the specular reflection by analyzing the distribution of observed pixel colors in the red-green-blue (RGB) color space [23]. Subsequent studies have improved highlight removal by combining the dichromatic reflectance model with chromaticity analysis [24], double edge-preserving filter [25], global optimization method [26], priority region filling [27], and neural network [28]. However, these methods often rely on prior knowledge and entail higher computational costs.…”

Section: Introductionmentioning

confidence: 99%

Computational ghost imaging with adaptive intensity illumination for scenes featuring specular surfaces

Xiong,

Zhang,

et al. 2024

J. Opt.

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Imaging a target scene with specular surfaces is a daunting challenge for both direct imaging and indirect computational imaging techniques. The intense specular reflection component during the measurement severely degrades the quality of the reconstructed image, resulting in a substantial loss of scene information. To address this issue, we propose a computational ghost imaging （CGI） method with adaptive intensity illumination. Capitalizing on the encoded imaging feature of CGI, this method enables effective imaging of target scenes with specular surfaces through two series of measurements, eliminating the necessity for additional optical components. Based on the position and intensity information of pixels in the specular regions from the first series of measurements, our method modulates the illumination patterns to weaken the intensity of the specular region in the second series of measurements. Simulation and experimental results demonstrate that the utilization of these modulated illumination patterns for target scene measurement effectively mitigates interference from the specular surface during imaging. Consequently, the reconstructed image is capable of presenting more detailed information about the target scene other than the specular regions. Our work introduces a novel approach for imaging target scenes with specular surfaces and broadens the scope of applications for CGI in reality.

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A Specular Removal Algorithm Based on Improved Specular-free Image and Chromaticity Analysis

Cited by 3 publications

References 12 publications

Deep Highlight Removal Using Temporal Dark Prior in High-Speed Domain

Deep Highlight Removal Using Temporal Dark Prior in High-Speed Domain

Joint Deep Estimation of Intrinsic and Dichromatic Image Decomposition

Computational ghost imaging with adaptive intensity illumination for scenes featuring specular surfaces

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