Non-Uniform Deblurring in HDR Image Reconstruction

• Published in: IEEE transactions on image processing Vol. 22; no. 10; pp. 3739 - 3750
• Main Authors: Vijay, Channarayapatna Shivaram, Paramanand, Chandramouli, Rajagopalan, Ambasamudram Narayanan, Chellappa, Rama
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Blurred; Blurring; Cameras; Computational photography; Exact sciences and technology; high dynamic range imaging; image deblurring; Image processing; Information, signal and communications theory; Irradiance; Mathematical models; motion blur; Nonuniform; Product introduction; Signal processing; Spreads; Telecommunications and information theory; Dynamic response; Image processing; image deblurring; Irradiance; Image restoration; Blurred image; Point spread function; Image reconstruction; Multiple image; Photography; HDR image; high dynamic range imaging; Spread function; Imaging; Organic conductor; Portable equipment; Exposure time; Computational photography; motion blur
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2013.2257809

Hand-held cameras inevitably result in blurred images caused by camera-shake, and even more so in high dynamic range imaging applications where multiple images are captured over a wide range of exposure settings. The degree of blurring depends on many factors such as exposure time, stability of the platform, and user experience. Camera shake involves not only translations but also rotations resulting in nonuniform blurring. In this paper, we develop a method that takes input non-uniformly blurred and differently exposed images to extract the deblurred, latent irradiance image. We use transformation spread function (TSF) to effectively model the blur caused by camera motion. We first estimate the TSFs of the blurred images from locally derived point spread functions by exploiting their linear relationship. The scene irradiance is then estimated by minimizing a suitably derived cost functional. Two important cases are investigated wherein 1) only the higher exposures are blurred and 2) all the captured frames are blurred.