Grenoble Institute of Technology

About: Grenoble Institute of Technology is a education organization based out in Grenoble, France. It is known for research contribution in the topics: Hyperspectral imaging & Geology. The organization has 3427 authors who have published 5345 publications receiving 137158 citations. The organization is also known as: Grenoble INP.

A Benchmarking Protocol for Pansharpening: Dataset, Preprocessing, and Quality Assessment

Abstract: Comparative evaluation is a requirement for reproducible science and objective assessment of new algorithms. Reproducible research in the field of pansharpening of very high resolution images is a difficult task due to the lack of openly available reference datasets and protocols. The contribution of this article is threefold, and it defines a benchmarking framework to evaluate pansharpening algorithms. First, it establishes a reference dataset, named PAirMax , composed of 14 panchromatic and multispectral image pairs collected over heterogeneous landscapes by different satellites. Second, it standardizes various image preprocessing steps, such as filtering, upsampling, and band coregistration, by providing a reference implementation. Third, it details the quality assessment protocols for reproducible algorithm evaluation.

A critical comparison of pansharpening algorithms

Abstract: In this paper state-of-the-art and advanced methods for multispectral pansharpening are reviewed and evaluated on two very high resolution datasets acquired by IKONOS-2 (four bands) and WorldView-2 (eight bands). The experimental analysis allows us to highlight the performances of the two main pansharpening approaches (i.e. component substitution and multiresolution analysis).

From Text Detection in Videos to Person Identification

Abstract: We present in this article a video OCR system that detects and recognizes overlaid texts in video as well as its application to person identification in video documents. We proceed in several steps. First, text detection and temporal tracking are performed. After adaptation of images to a standard OCR system, a final post-processing combines multiple transcriptions of the same text box. The semi-supervised adaptation of this system to a particular video type (video broadcast from a French TV) is proposed and evaluated. The system is efficient as it runs 3 times faster than real time (including the OCR step) on a desktop Linux box. Both text detection and recognition are evaluated individually and through a person recognition task where it is shown that the combination of OCR and audio (speaker) information can greatly improve the performances of a state of the art audio based person identification system.

PinaVM: a systemC front-end based on an executable intermediate representation

Abstract: SystemC is the de facto standard for high-level modeling embedded systems. It allows system design at various levels of abstractions, provides typical object-orientation features and incorporates timing and concurrency concepts. A SystemC program is typically processed by a SystemC front-end in order to verify, debug and/or optimize the architecture. Designing a SystemC front-end is a difficult task and existing approaches suffer from limitations. In this paper, we present a new approach that addresses most of these limitations. We detail this approach, based on an executable intermediate representation. We introduce PinaVM, a new, open-source SystemC front-end and implementation of our contributions. We give experimental results on this tool