Blocking artifact removal using partial overlapping based on exact Legendre moments computation

Bahaoui, Zaineb; Zenkouar, Khalid; Fadili, Hakim El; Qjidaa, Hassan; Zarghili, Arsalane

doi:10.1007/s11554-014-0465-3

Cited by 6 publications

(3 citation statements)

References 26 publications

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“…Fractional-order Zernike moments have been used efficiently in plant disease recognition [24]. Legendre moments were used in [25] to reduce block artifacts. For image analysis, Zernike and Legendre polynomials are used as kernel functions for Zernike and Legendre moments, respectively [26].…”

Section: Literature Review and Discussionmentioning

confidence: 99%

Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

et al. 2022

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Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face image datasets, ORL and FEI. Different state-of-the-art face recognition methods were compared with the proposed method in order to evaluate its accuracy. We demonstrate that the proposed method achieves the highest recognition rate in different considered scenarios. Based on the obtained results, it can be seen that the proposed method is robust against noise and significantly outperforms previous approaches in terms of speed.

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Section: Literature Review and Discussionmentioning

confidence: 99%

Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

et al. 2022

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“…In [22], a blocking artifact detection method was proposed for motion-compensated frame-rate upconversion algorithms. In [23], the authors presented the design of a partial overlapping block using exact Legendre moment computation for gray-level image reconstruction. ere have also been several researches with respect to image compression [24][25][26][27].…”

Section: Related Workmentioning

confidence: 99%

Improving the Quality of Left-Behind Children’s Participation in Sports through Wireless Network Monitoring

Zhao

2021

Mobile Information Systems

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Urbanization is the process that people shift from rural to urban areas, which has led to large numbers of left-behind children in China. The left-behind children stay in rural regions of China while their parents work in urban areas. The left-behind children have few opportunities to participate in sports due to the lacking of concern, and it is not of high quality even though they participate in sports. Therefore, it is necessary to improve the quality of left-behind children's sports participation through wireless network monitoring. Wireless network monitoring transmits high-definition (HD) video streaming in real time to facilitate feedback timely. This paper studies the two-dimensional (2D) integer discrete cosine transform (DCT) and analyzes the reason for image distortion, then an improved DCT coefficient quantization approach is proposed for long-distance real-time transmission of HD video streaming, and a noise processing with a zero-mean noise processing is added in optimized approach to solve the image distortion problem. The experimental results show that the proposed improved approach has a good performance in reducing the blocking artifacts, and within the image reconstruction, the proposed approach improves the subjective video quality.

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“…Two works [15] and [19], have proved that an overlapping window size of one pixel is the most effective in terms of image quality and time consuming.…”

Section: Overlapping Blocks Reconstruction Using Exact Momentsmentioning

confidence: 99%

Comparative Study of Exact Continuous Orthogonal Moments Applications : Local Feature Extraction and Data Compression

Bahaoui

Benouini

Fadili

et al. 2017

TMLAI

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This paper present an improved reconstruction algorithm of the multigray level images based on overlapping block method using exact continuous moments computation: Legendre , Zernike, Pseudo Zernike and Gegenbauer moments . We solve the artifact issue caused by unitary block reconstruction which affects the visual image quality. This method aim to ensure high accuracy and low computation time, using only small finite number of moments. Our approaches aims to introduce these moments in the field of data compression and local feature extraction for pattern recognition. Experimental results show the superiority of our proposed approaches over the existing methods.

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Blocking artifact removal using partial overlapping based on exact Legendre moments computation

Cited by 6 publications

References 26 publications

Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments

Improving the Quality of Left-Behind Children’s Participation in Sports through Wireless Network Monitoring

Comparative Study of Exact Continuous Orthogonal Moments Applications : Local Feature Extraction and Data Compression

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