Robust local stereo matching under varying radiometric conditions

Qu, Yufu; Jiang, Jixiang; Deng, Xin; Zheng, Yao

doi:10.1049/iet-cvi.2013.0117

Cited by 16 publications

(8 citation statements)

References 31 publications

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“…Research towards the use of a maximum a posteriori estimation [24] based stereo matching to compute the disparity of the pixels in different radiometric changes was also presented. Initially, a prior on the disparities of a few pixels is built.…”

Section: Literature Reviewmentioning

confidence: 99%

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Performance analysis of a fuzzy disparity selector for stereo matching of image segments under radiometric variations

Shetty¹,

George

Nayak

et al. 2020

Turk J Elec Eng & Comp Sci

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Stereo matching algorithms generate disparity maps, which contain the depth information of the environment, from two or more images of a scene taken from different viewpoints. The process of obtaining dense disparity maps is a problem which is still being actively researched. The presence of radiometric differences in the images only further complicates the stereo matching problem. In the present research work, the images are initially split into small patches of pixels, such that pixels in each patch have similar intensities. The authors attempt to study the effect of the parameters, namely, tuning parameter ' α ' and the number of segments, while the images are subjected to variations in exposure and illumination. The value ' α ' performs the function of a weight signifying the contribution of each data cost, when the two data costs are combined in a linear fashion. Lastly, the results of this methodology are compared with other methods that try to tackle the problem of stereo matching under radiometric variations.

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Section: Literature Reviewmentioning

confidence: 99%

“…Comparison of error values of disparity maps generated by the proposed method with other methods (different illumination conditions)[24].…”

mentioning

confidence: 99%

Performance analysis of a fuzzy disparity selector for stereo matching of image segments under radiometric variations

Shetty¹,

George

Nayak

et al. 2020

Turk J Elec Eng & Comp Sci

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“…Extensive simulations of test cases indicate that the wrong depth in occluded regions frequently appears as a large depth difference between neighboring pixels. To identify this condition, the x coordinate of the nearest pixel within a specific detection range (e.g., 8 pixels) with reliable depth is obtained as x nr if it exists, and then (9) is used to determine the reliability considering local occlusion (9) where T ld is a chosen threshold value for denoting a large depth difference between two nearby pixels, which is assumed to rarely appear in natural scenes. Fig.…”

Section: ) Minimum Cost Ambiguity Problem In Low-texture Regionsmentioning

confidence: 99%

Depth-Reliability-Based Stereo-Matching Algorithm and Its VLSI Architecture Design

Yang

Chu

Chen

et al. 2015

IEEE Trans. Circuits Syst. Video Technol.

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A low-complexity depth-reliability-based stereomatching algorithm and an efficient scanline memory-merging implementation scheme are proposed in this paper. The developed algorithm analyzes the accuracy of disparity results by using simple local window-based methods and preserves reliable information only. A bidirectional depth propagation flow is then adopted to fill the unreliable segments by using reliable information. Moreover, a set of predefined function-specific reliability variables are extracted to further improve depth quality in the occluded and smooth regions, which can reduce 39% bad pixels obtained by applying the basic 7 × 7 window-based matching. The proposed scanline memory-merging scheme along with data prefetching can lead to 32.7% savings on the scanline memory area and relax the requirements of external frame buffer size and bandwidth. Experimental results show that the implemented stereo-matching hardware has a gate count of 223 k including the scanline memory, and can achieve up to 70 frames/s for 480 × 540 resolution (2 × 2 downsampling of FullHD side-by-side 3-D format) with 56 disparity levels.Index Terms-Reliability-based computation, stereo-matching, window-based sum of absolute differences (SAD) architecture.

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“…Compared with global methods, local methods are often less time-consuming. However, their computational efficiency usually comes at the expense of reduced matching accuracy and increased sensitivity to noise [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Forward-Backward Diffusion and Pruning-Based Cost Aggregation for Non-Local Stereo Matching

Xu¹,

Yang²,

Zuo³

et al. 2022

Advances in Transdisciplinary Engineering

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Minimum spanning tree (MST) has been devised for non-local cost aggregation to solve the stereo matching problem. However, the cost aggregation is employed directly from leaf toward root node, then in an inverse pass without considering any decision rules. And a small amount of noise is also existed in stereo image pairs. Both of the limitations often lead to failure in achieving more competitive results. This paper presents a novel stereo matching algorithm using forward-backward diffusion and pruning-based cost aggregation. In “forward-backward” process, the raw image pairs are smoothened on a horizontal tree structure as well as retaining image edges sharp. During cost aggregation, the MST where a complete graph involves the whole image pixels is cut off self-adaptively when the depth edge information is referred to. Each node in this tree receives supports from all other nodes which belong to similar depth regions. Meanwhile, an enhanced edge similarity function between two nearest neighboring nodes is formulated to deal with the small-weight-accumulation problem in textureless regions. Consequently, the cost volume can be well aggregated. The proposed method is demonstrated on Middlebury v.2 & v.3 datasets and can obtain good performance in disparity accuracy compared with other five MST based stereo matching methods.

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Robust local stereo matching under varying radiometric conditions

Cited by 16 publications

References 31 publications

Performance analysis of a fuzzy disparity selector for stereo matching of image segments under radiometric variations

Performance analysis of a fuzzy disparity selector for stereo matching of image segments under radiometric variations

Depth-Reliability-Based Stereo-Matching Algorithm and Its VLSI Architecture Design

Forward-Backward Diffusion and Pruning-Based Cost Aggregation for Non-Local Stereo Matching

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