Browsing by Author "Thoreau D."

Now showing 1 - 2 of 2

Citation - WoS: 2
Citation - Scopus: 3
Block Prediction Using Approximate Template Matching
(Institute of Electrical and Electronics Engineers Inc., 2015) Zepeda J.; Türkan, Mehmet; Thoreau D.
Template matching methods have been shown to offer bit-rate savings of up to 15% when used for in-loop prediction in compression. Yet the required nearest-template search process results in prohibitive complexity. Hence, in this paper we use approximate nearest neighbor search methods to successfully address this drawback of template matching methods. Our approach uses a template index that is updated during the decoding process, yet the incurred overhead pays off in reduced nearest-template search complexity, resulting in a significant gain in template search complexity. Rate-distortion experiments further indicate that there is no rate-distortion penalty resulting from our proposed approximate template search method, and in fact a small gain of 0.1 dB is observed. © 2015 EURASIP.
Citation - WoS: 1
Citation - Scopus: 2
Epitomic Image Factorization Via Neighbor-Embedding
(IEEE Computer Society, 2015) Türkan, Mehmet; Alain M.; Thoreau D.; Guillotel P.; Guillemot C.
We describe a novel epitomic image representation scheme that factors a given image content into a condensed epitome and a low-resolution image to reduce the memory space for images. Given an input image, we construct a condensed epitome such that all image patches can successfully be reconstructed from the factored representation by means of an optimized neighbor-embedding strategy. Under this new scope of epitomic image representations aligned with the manifold sampling assumption, we end up a more generic epitome learning scheme with increased optimality, compactness, and reconstruction stability. We present the performance of the proposed method for image and video up-scaling (super-resolution) while extensions to other image and video processing are straightforward. © 2015 IEEE.