Parallax-Tolerant Image Stitching Based on Robust Elastic Warping

Li, Jing; Wang, Zhengming; Lai, Shupeng; Zhai, Yongping; Zhang, Maojun

doi:10.1109/tmm.2017.2777461

Cited by 202 publications

(172 citation statements)

References 39 publications

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“…Jing Li et.al. proposed the warping method that combined mesh based model with direct deformation scheme in [7]. The warping model successfully eliminates the parallax error and maintains alignment accuracy.…”

Section: Full and Reduced Reference Image Quality Assessment Of Panormentioning

confidence: 99%

“…The proposed method is tested on As-Projective-As-Possible Image Stitching Database [4] and compared with existing image stitching methods viz. As-Projective-A-Possible (APAP) [5], Shape Preserving Half Projective (SPHP) [6] and Elastic Local Alignment (ELA) [7]. The perceptual quality of stitched image is examined with the help of objective image quality assessment approach like FRIQA and RRIQA.…”

Section: Introductionmentioning

confidence: 99%

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Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method

Vaidya*,

Gandhe

2020

IJITEE

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Image Stitching is becoming more popular in field of computer vision because of rapid development of efficient algorithms that replaces the high cost wider lens cameras and commercial image stitching tools. The existing methods used global geometric transformation in registration stage and hence suffered from object deformation, parallax error, ghosting effect and motion blur in output result. In this paper, newly developed Hybrid Warping of weighted linearized homography matrix and similarity transform matrix is implemented over standard image stitching database. The visual quality of stitched image using proposed method has been examined in terms of performance metrics of Full Reference Image Quality Assessment (FRIQA) such as Root Mean Square Error (RMSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Reduced Reference Image Quality Assessment (RRIQA). Also, the performance analysis of proposed method is compared against existing image stitching methods in terms of field of view and stitching time. This analysis has ascertained the outperformance of Novel Hybrid Image Stitching method.

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Section: Full and Reduced Reference Image Quality Assessment Of Panormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method

Vaidya*,

Gandhe

2020

IJITEE

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“…We next prove that u 1 and v 1 are also incoherent vectors. Indeed, from (29), taking · ∞ on both sides yields…”

Section: Supplementary Documentmentioning

confidence: 99%

“…Other feature-based methods have focused on aspects of research somewhat adjacent to the topic of this paper such as 3D reconstruction, improving the aesthetic value of the stitched images, handling specific scenarios such as large parallax and low textures etc. These include [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], to name a few.…”

mentioning

confidence: 99%

Robust Alignment for Panoramic Stitching Via an Exact Rank Constraint

Tofighi

Monga

2019

IEEE Trans. on Image Process.

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We study the problem of image alignment for panoramic stitching. Unlike most existing approaches that are feature-based, our algorithm works on pixels directly, and accounts for errors across the whole images globally. Technically, we formulate the alignment problem as rank-1 and sparse matrix decomposition over transformed images, and develop an efficient algorithm for solving this challenging non-convex optimization problem. The algorithm reduces to solving a sequence of subproblems, where we analytically establish exact recovery conditions, convergence and optimality, together with convergence rate and complexity. We generalize it to simultaneously align multiple images and recover multiple homographies, extending its application scope towards vast majority of practical scenarios. Experimental results demonstrate that the proposed algorithm is capable of more accurately aligning the images and generating higher quality stitched images than state-of-the-art methods.

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“…In the existing algorithm, there are two disadvantages. First, the homography calculates feature points randomly selected from the set of feature matching points, and then it is judged whether most of the feature points satisfy the calculated homography transformation model [16][17][18]. If they are satisfied, the image is registered with this homography.…”

Section: Introductionmentioning

confidence: 99%

Improved Parallax Image Stitching Algorithm Based on Feature Block

Shi

Tan

et al. 2019

Symmetry

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Image stitching aims at generating high-quality panoramas with the lowest computational cost. In this paper, we present an improved parallax image-stitching algorithm using feature blocks (PIFB), which achieves a more accurate alignment and faster calculation speed. First, each image is divided into feature blocks using an improved fuzzy C-Means (FCM) algorithm, and the characteristic descriptor of each feature block is extracted using scale invariant feature transform (SIFT). The feature matching block of the reference image and the target image are matched and then determined, and the image is pre-registered using the homography calculated by the feature points in the feature block. Finally, the overlapping area is optimized to avoid ghosting and shape distortion. The improved algorithm considering pre-blocking and block stitching effectively reduced the iterative process of feature point matching and homography calculation. More importantly, the problem that the calculated homography matrix was not global has been solved. Ghosting and shape warping are significantly eliminated by re-optimizing the overlap of the image. The performance of the proposed approach is demonstrated using several challenging cases.

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Parallax-Tolerant Image Stitching Based on Robust Elastic Warping

Cited by 202 publications

References 39 publications

Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method

Full and Reduced Reference Image Quality Assessment of Panoramic View using Novel Hybrid Image Stitching Method

Robust Alignment for Panoramic Stitching Via an Exact Rank Constraint

Improved Parallax Image Stitching Algorithm Based on Feature Block

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