Laser & Optoelectronics Progress, Volume. 57, Issue 22, 220002(2020)
End-to-End Learning-Based Image Compression: A Review
In the big data era, we have witnessed the explosive growth of deep learning based image and video compression technologies. Such end-to-end learning-based compression frameworks have demonstrated promising efficiency for compact representation of original image data, and attracted a vast attention from both academia and industry. A systematic review of transformation, quantization, entropy coding, and loss function used in end-to-end learning-based image compression framework is introduced in this work. The research progress and key technologies are briefly introduced, as well as the comparative studies of coding performance for existing methods with leading efficiency.
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Jimin Chen, Zehao Lin. End-to-End Learning-Based Image Compression: A Review[J]. Laser & Optoelectronics Progress, 2020, 57(22): 220002
Category: Reviews
Received: Dec. 18, 2019
Accepted: Apr. 17, 2020
Published Online: Nov. 5, 2020
The Author Email: Lin Zehao (lzhtocoffee@163.com)