MPI for Intelligent Systems - Pixel Group

MPI-IS - Pixel Group

Abstract

Camera lenses are a critical component of optical imaging systems, and lens imperfections compromise image quality. While traditionally, sophisticated lens design and quality control aim at limiting optical aberrations, recent works promote the correction of optical flaws by computational means. These approaches rely on elaborate measurement procedures to characterize an optical system, and perform image correction by non-blind deconvolution. In this paper, we present a method that utilizes physically plausible assumptions to estimate non-stationary lens aberrations blindly, and thus can correct images without knowledge of specifics of camera and lens. The blur estimation features a novel preconditioning step that enables fast deconvolution. We obtain results that are competitive with state-of-the-art non-blind approaches.

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Example Images

Photo taken with self-built lens

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Blurry

Schuler et al.

Adobe

Ours

Comparison with non-blind approaches

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Kee et al.

DXO

Ours

Historical image from 1940

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Adobe

Ours

Canon 24mm f/1.4

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Schuler et al.

Ours