IEEE Trans Image Process - Commutability of blur and affine warping in super-resolution with application to joint estimation of triple-coupled variables.

Tópicos

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Resumo

This paper proposes a new approach to the image blind super-resolution (BSR) problem in the case of affine interframe motion. Although the tasks of image registration, blur identification, and high-resolution (HR) image reconstruction are coupled in the imaging process, when dealing with nonisometric interframe motion or without the exact knowledge of the blurring process, classic SR techniques generally have to tackle them (maybe in some combinations) separately. The main difficulty is that state-of-the-art deconvolution methods cannot be straightforwardly generalized to cope with the space-variant motion. We prove that the operators of affine warping and blur commute with some additional transforms and derive an equivalent form of the BSR observation model. Using this equivalent form, we develop an iterative algorithm to jointly estimate the triple-coupled variables, i.e., the motion parameters, blur kernels, and HR image. Experiments on synthetic and real-life images illustrate the performance of the proposed technique in modeling the space-variant degradation process and restoring local textures.

Resumo Limpo

paper propos new approach imag blind superresolut bsr problem case affin interfram motion although task imag registr blur identif highresolut hr imag reconstruct coupl imag process deal nonisometr interfram motion without exact knowledg blur process classic sr techniqu general tackl mayb combin separ main difficulti stateoftheart deconvolut method straightforward general cope spacevari motion prove oper affin warp blur commut addit transform deriv equival form bsr observ model use equival form develop iter algorithm joint estim triplecoupl variabl ie motion paramet blur kernel hr imag experi synthet reallif imag illustr perform propos techniqu model spacevari degrad process restor local textur

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