Binary Sparse Representation Based on Arbitrary Quality Metrics and Its Applications

Takahiro OGAWA  Sho TAKAHASHI  Naofumi WADA  Akira TANAKA  Miki HASEYAMA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E101-A   No.11   pp.1776-1785
Publication Date: 2018/11/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E101.A.1776
Type of Manuscript: Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)
Category: Image, Vision
image approximation,  binary sparse representation,  image quality metrics,  visual saliency,  

Full Text: PDF(25.9MB)
>>Buy this Article

Binary sparse representation based on arbitrary quality metrics and its applications are presented in this paper. The novelties of the proposed method are twofold. First, the proposed method newly derives sparse representation for which representation coefficients are binary values, and this enables selection of arbitrary image quality metrics. This new sparse representation can generate quality metric-independent subspaces with simplification of the calculation procedures. Second, visual saliency is used in the proposed method for pooling the quality values obtained for all of the parts within target images. This approach enables visually pleasant approximation of the target images more successfully. By introducing the above two novel approaches, successful image approximation considering human perception becomes feasible. Since the proposed method can provide lower-dimensional subspaces that are obtained by better image quality metrics, realization of several image reconstruction tasks can be expected. Experimental results showed high performance of the proposed method in terms of two image reconstruction tasks, image inpainting and super-resolution.