Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach

Ma, Ning; Men, Yubo; Men, Chaoguang; Li, Xiang

doi:10.3390/sym8120159

Cited by 29 publications

(9 citation statements)

References 35 publications

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“…We have compared our results with recently published methods (i.e. [4–8 ]) to show the competitiveness of the proposed method in this Letter. Their method were developed with different framework architectures including the deep learning method in [9 ].…”

Section: Introductionmentioning

confidence: 94%

Improvement of disparity map refinement stage using adaptive least square plane fitting technique

Hamzah

Ibrahim

2020

Electronics Letters

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This Letter presents an improvement of disparity map refinement stage using adaptive least square plane fitting technique. This technique is proposed to increase the accuracy on the final stage of stereo matching algorithm. Fundamentally, the accuracy of matching process depends on the robustness of an algorithm on the plain colour region, depth discontinuity and repetitive pattern area. These regions are difficult to be matched and very challenging. Thus, this Letter proposes multiple point selections of disparities on a plane to adaptively group similar disparity values. Then, the distance of each disparity is calculated to ensure the values are accurately grouped. The distance refers to an assigned reference radius disparity location. Based on the experimental results using the KITTI and Middlebury benchmark images, the proposed method is capable of increasing the accuracy on the challenging regions and the quantitative measurement.

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Section: Introductionmentioning

confidence: 94%

Improvement of disparity map refinement stage using adaptive least square plane fitting technique

Hamzah

Ibrahim

2020

Electronics Letters

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“…Additionally, it shows that the proposed stereo matching algorithm in this Letter is competitive with some recently published methods in the Middlebury and KITTI databases. 12.05 11.45 [5] 12.30 8.97 [6] 12.70 8.81 [7] 22.30 12.00 17.02 16.85 [8] 19.61 18.76 [9] 25.01 24.67 [10] 45.83 45.46…”

Section: Cost Aggregation and Disparity Computationmentioning

confidence: 99%

Improvement of stereo matching algorithm based on sum of gradient magnitude differences and semi‐global method with refinement step

Hamzah

Ibrahim

2018

Electron. lett.

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A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed. The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. To get over these problems, sum of gradient magnitude differences has been introduced at the first stage. This method is strong against the radiometric differences on the stereo images. Hence, this approach will reduce the error of preliminary data for stereo corresponding process. The SGM is used at the aggregation, and optimisation stage uses 16 different directions of 2D path. Additionally, the iterative guided filter is utilised at the refinement stage which minimises the errors and increases the accuracy. The proposed work produces accurate results and performs much better compared with some established algorithms based on the standard stereo benchmarking evaluation from the Middlebury and KITTI.

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“…In common, Winner-Takes-All (WTA) strategy is applied for local based optimization. It is low computational complexity and fast execution time [17][18][19]. Local method such implemented in [20] that used fitting the plane to increase the accuracy at the final stage.…”

Section: Introductionmentioning

confidence: 99%

A study of edge preserving filters in image matching

et al. 2021

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This article presents a study on edge preserving filters in image matching which comprises a development of stereo matching algorithm using two edge preserving filters. Fundamentally, the framework is reconstructed by several sequential processes. The output of these processes is a disparity map or depth map. The corresponding points between two images require accurate matching to make accurate depth map estimation. Thus, the propose work in this article utilizes sum of squared differences (SSD) with dual edge preserving filters. These filters are used due to edge preserved properties and to increase the accuracy. The median filter (MF) and bilateral filter (BF) will be utilized. The SSD produces preliminary results with low noise and the edge preserving filters reduce noise on the low texture regions with edge preserving properties. Based on the experimental analysis using the standard benchmarking evaluation system from the Middlebury, the disparity map produced is 6.65% for all error pixels. It shows an accurate edge preserved properties on the disparity maps. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it displays the proposed work in this article perform much better.

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Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach

Cited by 29 publications

References 35 publications

Improvement of disparity map refinement stage using adaptive least square plane fitting technique

Improvement of disparity map refinement stage using adaptive least square plane fitting technique

Improvement of stereo matching algorithm based on sum of gradient magnitude differences and semi‐global method with refinement step

A study of edge preserving filters in image matching

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