Entropy-Based Combined Metric for Automatic Objective Quality Assessment of Stitched Panoramic Images

Okarma, Krzysztof; Chlewicki, Wojciech; Kopytek, Mateusz; Marciniak, Beata

doi:10.3390/e23111525

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…Bakurov et al [ 53 ] revisited the classical SSIM [ 29 ] and MS-SSIM [ 34 ] metrics by applying evolutionary and swarm intelligence optimization methods to find optimal hyperparameters for SSIM and MS-SSIM instead of the original settings. Fusion-based metrics were also proposed for remote sensing images [ 54 ], stitched panoramic images [ 55 ], and 3D image quality assessment [ 18 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Full-Reference Image Quality Assessment Based on an Optimal Linear Combination of Quality Measures Selected by Simulated Annealing

Varga

2022

J. Imaging

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Digital images can be distorted or contaminated by noise in various steps of image acquisition, transmission, and storage. Thus, the research of such algorithms, which can evaluate the perceptual quality of digital images consistent with human quality judgement, is a hot topic in the literature. In this study, an image quality assessment (IQA) method is introduced that predicts the perceptual quality of a digital image by optimally combining several IQA metrics. To be more specific, an optimization problem is defined first using the weighted sum of a few IQA metrics. Subsequently, the optimal values of the weights are determined by minimizing the root mean square error between the predicted and ground-truth scores using the simulated annealing algorithm. The resulted optimization-based IQA metrics were assessed and compared to other state-of-the-art methods on four large, widely applied benchmark IQA databases. The numerical results empirically corroborate that the proposed approach is able to surpass other competing IQA methods.

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Section: Literature Reviewmentioning

confidence: 99%

Full-Reference Image Quality Assessment Based on an Optimal Linear Combination of Quality Measures Selected by Simulated Annealing

Varga

2022

J. Imaging

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“…MSR+SIFT and MSR+AKAZE exhibit the best results for all threshold values. On the other hand, the Spearman's rank correlation coefficient (SRCC [39]) analysis was performed, which indicates the level of correlation that exists between two variables, in our case, the number of detectors obtained and the number of splices performed correctly, which is defined by Equation (13), where ρ = Pearson correlation coefficient, d 2 i = difference between the two ranks of each observation and n = number of observations. To perform this evaluation, we used the values shown in the last column of Table 1.…”

Section: Quantitative Evaluation For a Variety Of Scenesmentioning

confidence: 99%

Analysis of Different Image Enhancement and Feature Extraction Methods

et al. 2022

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This paper describes an image enhancement method for reliable image feature matching. Image features such as SIFT and SURF have been widely used in various computer vision tasks such as image registration and object recognition. However, the reliable extraction of such features is difficult in poorly illuminated scenes. One promising approach is to apply an image enhancement method before feature extraction, which preserves the original characteristics of the scene. We thus propose to use the Multi-Scale Retinex algorithm, which is aimed to emulate the human visual system and it provides more information of a poorly illuminated scene. We experimentally assessed various combinations of image enhancement (MSR, Gamma correction, Histogram Equalization and Sharpening) and feature extraction methods (SIFT, SURF, ORB, AKAZE) using images of a large variety of scenes, demonstrating that the combination of the Multi-Scale Retinex and SIFT provides the best results in terms of the number of reliable feature matches.

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“…In order to improve the quality and performance of stitching, many researchers have introduced the concepts of entropy and information theory into image stitching [ 23 , 24 ]. Among existing research, some methods utilize entropy or information theory to select appropriate features for matching.…”

Section: Introductionmentioning

confidence: 99%

Research on Image Stitching Algorithm Based on Point-Line Consistency and Local Edge Feature Constraints

Ma,

Li,

Liu

et al. 2024

Entropy

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Image stitching aims to synthesize a wider and more informative whole image, which has been widely used in various fields. This study focuses on improving the accuracy of image mosaic and proposes an image mosaic method based on local edge contour matching constraints. Because the accuracy and quantity of feature matching have a direct influence on the stitching result, it often leads to wrong image warpage model estimation when feature points are difficult to detect and match errors are easy to occur. To address this issue, the geometric invariance is used to expand the number of feature matching points, thus enriching the matching information. Based on Canny edge detection, significant local edge contour features are constructed through operations such as structure separation and edge contour merging to improve the image registration effect. The method also introduces the spatial variation warping method to ensure the local alignment of the overlapping area, maintains the line structure in the image without bending by the constraints of short and long lines, and eliminates the distortion of the non-overlapping area by the global line-guided warping method. The method proposed in this paper is compared with other research through experimental comparisons on multiple datasets, and excellent stitching results are obtained.

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Entropy-Based Combined Metric for Automatic Objective Quality Assessment of Stitched Panoramic Images

Cited by 7 publications

References 26 publications

Full-Reference Image Quality Assessment Based on an Optimal Linear Combination of Quality Measures Selected by Simulated Annealing

Full-Reference Image Quality Assessment Based on an Optimal Linear Combination of Quality Measures Selected by Simulated Annealing

Analysis of Different Image Enhancement and Feature Extraction Methods

Research on Image Stitching Algorithm Based on Point-Line Consistency and Local Edge Feature Constraints

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