Dick, João Atz

English

Lume 5.8

Evento Salão UFRGS 2021: SIC - XXXIII SALÃO DE INICIAÇÃOCIENTÍFICA DA UFRGSAno 2021Local VirtualTítulo QUALITY AND COMPLEXITY ASSESSMENT OF LEARNING-BASEDIMAGE COMPRESSION SOLUTIONSAutor JOÃO ATZ DICKOrientador SERGIO BAMPIQUALITY AND COMPLEXITY ASSESSMENT OF LEARNING-BASED IMAGE COMPRESSION SOLUTIONS João Dick1, Brunno Abreu1, Mateus Grellert2, Sergio Bampi1 1Informatics Institute (PGMICRO), Federal University of Rio Grande do Sul, Porto Alegre, Brazil 2Graduate Program in Computer Science, Federal University of Santa Catarina, Florianópolis, Brazil The demand for multimedia services has experienced a huge increase in the latest years, making image and video content account for most of the web’s data traffic. To address this issue, compression solutions are of utmost importance. When compressing an image, the main goal is to reduce the image file size as much as possible with minimal loss of quality, which has to be quantified by a particular visual quality metric. This work presents an analysis of state-of-the-art learning-based image compression techniques. We compare 8 models available in the Tensorflow Compression package in terms of visual quality metrics and processing time, using the KODAK data set. The results are compared with the Better Portable Graphics (BPG) and the JPEG2000 codecs. Results show that JPEG2000 has the lowest execution times compared with the fastest learning-based model, with a speedup of 1.46x in compression and 30x in decompression. However, the learning-based models achieved improvements over JPEG2000 in terms of quality, especially for lower bitrates. Our findings also show that BPG is more efficient in terms of PSNR, but the learning models are better for other quality metrics, and sometimes even faster. The results indicate that learning-based techniques are promising solutions. The paper that resulted from this work was accepted at the 2021 IEEE International Conference on Image Processing (ICIP) and can be seen at https://arxiv.org/abs/2107.09136. 

Quality and complexity assessment of learning-based image compression solutions

https://lume.ufrgs.br/bitstream/10183/245081/1/Resumo_75249.pdf

Quality and complexity assessment of learning-based image compression solutions

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Lume 5.8