Wavelet transform based on Meyer algorithm for image edge and blocking artifact reduction

Wu, Ming-Te

doi:10.1016/j.ins.2018.09.058

Cited by 19 publications

(12 citation statements)

References 8 publications

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“…In [20], a new method of image upscaling along with deblocking of compressed images was proposed. In [21], a wavelet transform based on the Meyer algorithm with edgeangle tracking capability was proposed for edge and blocking artifact reduction of an image, during image compression processes. In [22], a blocking artifact detection method was proposed for motion-compensated frame-rate upconversion algorithms.…”

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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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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“…The wavelet transform (WT) is a transformation technique that represents the time and frequency components for signals, in which the frequency component changes over time [21,22]. In general, the Fourier transform indicates the frequency components under the assumption that the signals do not change over time.…”

Section: Wavelet Transformsmentioning

confidence: 99%

Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals

Jang

Lee

2020

Symmetry

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In this study, techniques were proposed for the detection of epileptic seizures from electroencephalogram (EEG) signals using the wavelet transform (WT), peak extraction and phase–space reconstruction (PSR) based Euclidean distances. In the first step, the wavelet coefficients were extracted after eliminating the noise from the EEG signals using a WT, which is a widely used signal processing technique. In the second step, the peaks were extracted from the wavelet coefficients. In the third step, the continuous peaks that were extracted were mapped to 3D coordinates using PSR. In the fourth step, the Euclidean distances between the mapped 3D coordinates and the origin were obtained. The features of the Euclidean distances obtained were extracted using statistical techniques. The final features extracted were used as inputs to the neural network with weighted fuzzy membership (NEWFM). NEWFM contains the bounded sum of weighted fuzzy memberships (BSWFMs) that can reveal the differences in the graphic characteristics between normal EEG signals and epileptic-seizure EEG signals. The BSWFMs can easily be embedded in a portable device to detect epileptic seizures from EEG signals in real life.

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“…Shape-adaptive discrete cosine transform (SA-DCT) [9] is widely considered as the state-of-the-art deblocking-oriented algorithm, but like many other deblocking-oriented algorithms, it may produce vague effects and is not able to maintain the sharp edges of the original images. Recently, Wu [14] proposed wavelet transform for blocking artifact reduction based on Meyer algorithm. Neural networks and deep learning currently provide the best solutions to many problems [10,11,[15][16][17].…”

Section: Related Workmentioning

confidence: 99%

Compression artifacts reduction by improved generative adversarial networks

Zhao

Sun

Yang

et al. 2019

J Image Video Proc.

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In this paper, we propose an improved generative adversarial network (GAN) for image compression artifacts reduction task (artifacts reduction by GANs, ARGAN). The lossy compression leads to quite complicated compression artifacts, especially blocking artifacts and ringing effects. To handle this problem, we choose generative adversarial networks as an effective solution to reduce diverse compression artifacts. The structure of "U-NET" style is adopted as the generative network in the GAN. A discriminator network is designed in a convolutional manner to differentiate the restored images from the ground truth distribution. This approach can help improve the performance because the adversarial loss aggressively encourages the output image to be close to the distribution of the ground truth. Our method not only learns an end-to-end mapping from input degraded image to corresponding restored image, but also learns a loss function to train this mapping. Benefit from the improved GANs, we can achieve desired results without hand-engineering the loss functions. The experiments show that our method achieves better performance than the state-of-the-art methods.

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Wavelet transform based on Meyer algorithm for image edge and blocking artifact reduction

Cited by 19 publications

References 8 publications

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

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

Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals

Compression artifacts reduction by improved generative adversarial networks

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