Concept

Transform coding

Publications associées (47)

Function Integration, Reconstruction And Approximation Using Rank-1 Lattices

We consider rank-1 lattices for integration and reconstruction of functions with series expansion supported on a finite index set. We explore the connection between the periodic Fourier space and the non-periodic cosine space and Chebyshev space, via tent ...

2021

Graph Transform Optimization With Application to Image Compression

Pascal Frossard, Giulia Fracastoro

In this paper, we propose a new graph-based transform and illustrate its potential application to signal compression. Our approach relies on the careful design of a graph that optimizes the overall rate-distortion performance through an effective graph-bas ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Benchmarking JPEG XL image compression

Touradj Ebrahimi, Evgeniy Upenik

JPEG XL is a practical, royalty-free codec for scalable web distribution and efficient compression of high-quality photographs. It also includes previews, progressiveness, animation, transparency, high dynamic range, wide color gamut, and high bit depth. U ...

SPIE2020

Graph-based Transform Coding with Application to Image Compression

Pascal Frossard, Giulia Fracastoro

In this paper, we propose a new graph-based coding framework and illustrate its application to image compression. Our approach relies on the careful design of a graph that optimizes the overall rate-distortion performance through an effective graph-based t ...

2019

MATHICSE Technical Report : Function integration, reconstruction and approximation using rank-1 lattices

Fabio Nobile, Giovanni Migliorati

MATHICSE2019

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants

Volkan Cevher, Catherine Dehollain, Mahsa Shoaran, Cosimo Aprile, Yusuf Leblebici, Luca Baldassarre, Kerim Türe, Gürkan Yilmaz, Franco Maloberti

Implantable systems are nowadays being used to interface the human brain with external devices, in order to understand and potentially treat neurological disorders. The most predominant design constraints are the system’s area and power. In this paper, we ...

2018

Statistically-Motivated Second-order Pooling

Mathieu Salzmann, Kaicheng Yu

Second-order pooling, a.k.a. bilinear pooling, has proven effective for deep learning based visual recognition. However, the resulting second-order networks yield a final representation that is orders of magnitude larger than that of standard, first-order ...

2018

Numerical experiments with MALDI Imaging data

Pierre Vandergheynst, Mohammad Golbabaee

This article does not present new mathematical results, it solely aims at discussing some numerical experiments with MALDI Imaging data. However, these experiments are based on and could not be done without the mathematical results obtained in the UNLocX p ...

Springer2014

Compressive Multichannel Cortical Signal Recording

Pierre Vandergheynst, Alexandre Schmid, Mahsa Shoaran, Yusuf Leblebici, Mahdad Hosseini Kamal

This paper presents a novel approach to acquire multichannel wireless intracranial neural data based on a compressive sensing scheme. The designed circuits are extremely compact and low-power which confirms the relevance of the proposed approach for multic ...

IEEE2013

Compressive Multichannel Cortical Signal Recording

Pierre Vandergheynst, Alexandre Schmid, Mahsa Shoaran, Yusuf Leblebici, Mahdad Hosseini Kamal

IEEE2013

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