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Most Influential CVPR 2000 Paper · 2026-03 edition

High Dynamic Range Imaging: Spatially Varying Pixel Exposures

S. K. Nayar and T. Mitsunaga

Venue
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2000
Recognition
Most Influential CVPR 2000 Paper (Rank No. 11)
Edition
2026-03
Impact factor
8
Certificate ID
294bf043ca2a0842

Abstract

While real scenes produce a wide range of brightness variations, vision systems use low dynamic range image detectors that typically provide 8 bits of brightness data at each pixel. The resulting low quality images greatly limit what vision can accomplish today. This paper proposes a very simple method for significantly enhancing the dynamic range of virtually any imaging system. The basic principle is to simultaneously sample the spatial and exposure dimensions of image irradiance. One of several ways to achieve this is by placing an optical mask adjacent to a conventional image detector array. The mask has a pattern with spatially varying transmittance, thereby giving adjacent pixels on the detector different exposures to the scene. The captured image is mapped to a high dynamic range image using an efficient image reconstruction algorithm. The end result is an imaging system that can measure a very wide range of scene radiance and produce a substantially larger number of brightness levels, with a slight reduction in spatial resolution. We conclude with several examples of high dynamic range images computed using spatially varying pixel exposures.

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