Publications related to Quantization (image processing)

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Bowen Huang

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

2023

Cascaded all-optical quantization employing step-size MMI and shape-optimized power splitter

Jijun He, Xiaowei Zhang, Jian Wu, Ye Tian

As a key unit of future high-throughput communications, optical analog to digital converter (OADC) with all-optical quantizer element that simultaneously possesses high resolution, large bandwidth and compact size is highly promising. A pending issue of co ...

ELSEVIER SCI LTD2023

Convex Quantization Preserves Logconcavity

Pol del Aguila Pla

A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

SPIE2022

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...

2021

Differentiable Patch Selection for Image Recognition

Jean-Baptiste Francis Marie Juliette Cordonnier, Aravindh Mahendran

Neural Networks require large amounts of memory and compute to process high resolution images, even when only a small part of the image is actually informative for the task at hand. We propose a method based on a differentiable Top-K operator to select the ...

IEEE COMPUTER SOC2021

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, Flavio Ponzina

Inferences using Convolutional Neural Networks (CNNs) are resource and energy intensive. Therefore, their execution on highly constrained edge devices demands the careful co-optimization of algorithms and hardware. Addressing this challenge, in this paper ...

2021

Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

Meritxell Bach Cuadra, Tobias Kober, Tom Hilbert, Thomas Yu, Sébastien Tourbier, Reto Meuli, Patric Hagmann, Hamza Kebiri

Accurate characterization of in utero human brain maturation is critical as it involves complex interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool complementary to the u ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

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Quantization (image processing)

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Cascaded all-optical quantization employing step-size MMI and shape-optimized power splitter

Towards learning-based image compression for storage on DNA support

Convex Quantization Preserves Logconcavity

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Differentiable Patch Selection for Image Recognition

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

Graph Chatbot

Chat with Graph Search

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Differentiable Patch Selection for Image Recognition

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

Convex Quantization Preserves Logconcavity

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Cascaded all-optical quantization employing step-size MMI and shape-optimized power splitter

Towards learning-based image compression for storage on DNA support

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction