In the last years, the development of compression algorithms for image collections (e.g., photo albums) has become very popular due to the enormous diffusion of digital photographs. Typically, current solutions create an image sequence from images of the photo album to make them suitable for compression using a High Performance Video Coding (HEVC) encoder. In this study, we investigated a different approach to compress a collection of similar images. Our main idea is to exploit the inter- and intra- patch redundancy to compress the entire set of images. In practice, our approach is equivalent to compress the image set with Vector Quantization (VQ) using a global codebook. Our tests show that our clusterization algorithm is effective for a large number of images.

Image sets compression via patch redundancy

Corsini M;Banterle F;Ponchio F;Cignoni P
2019

Abstract

In the last years, the development of compression algorithms for image collections (e.g., photo albums) has become very popular due to the enormous diffusion of digital photographs. Typically, current solutions create an image sequence from images of the photo album to make them suitable for compression using a High Performance Video Coding (HEVC) encoder. In this study, we investigated a different approach to compress a collection of similar images. Our main idea is to exploit the inter- and intra- patch redundancy to compress the entire set of images. In practice, our approach is equivalent to compress the image set with Vector Quantization (VQ) using a global codebook. Our tests show that our clusterization algorithm is effective for a large number of images.
2019
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
EUVIP 2019 - 8th European Workshop on Visual Information Processing
10
15
6
978-1-7281-4496-2
https://ieeexplore.ieee.org/document/8946237
IEEE
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
28-31 October 2019
Roma, Italy
Image compression
Image statistics
Photo album compression
Image collections
Clustering
Vector quantization
4
reserved
Corsini M.; Banterle F.; Ponchio F.; Cignoni P.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/374728
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