Residual learning based densely connected deep dilated network for joint deblocking and super resolution

Gadipudi Amaranageswarao; S. Deivalakshmi; Seok‐Bum Ko

doi:10.1007/s10489-020-01670-y

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Residual learning based densely connected deep dilated network for joint deblocking and super resolution

Gadipudi Amaranageswarao S. Deivalakshmi Seok‐Bum Ko

Year: 2020 Journal: Applied Intelligence Vol: 50 (7)Pages: 2177-2193 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-020-01670-y

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Keywords:

Computer science Deblocking filter Residual Artificial intelligence JPEG Convolution (computer science) Joint (building) Computer vision Deep learning Image compression Compression artifact Image (mathematics) Algorithm Image processing Artificial neural network

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Video Quality Assessment

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Residual learning based densely connected deep dilated network for joint deblocking and super resolution

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