Blur image processing
Date of Award
Ph.D. in Electrical Engineering
Department of Electrical and Computer Engineering
Advisor: Keigo Hirakawa
Image blur stems from camera sensor pixel recording light from multiple sources. There are three causes of blur: object motion, optical defocus and camera shake. We propose double discrete wavelet transform (DDWT) to simplify the motion object and optical defocus blur analysis. In particular, DDWT de-correlates the blur from unobserved sharp image and DDWT coefficients give intuitive representation of blur kernel. DDWT based blur detection, estimation and deblurring are proposed to handle object motion blur image corrupted by low/high noise and defocus blur image. For camera shake blur, we propose inertial measurement unit (IMU) based deblurring. IMU is a set of motion sensors can be used to record the camera motion trajectory' the source of camera shake blur. Proposed work solves image blind deblurring problem by incorporating existing blind deblurring algorithm with IMU measurement in a complementary manner, along with image-IMU synchronization, therefore can be generalized by adopting other blind deblurring.
Image stabilization, Digital images Deconvolution, Imaging systems Image quality, Electrical Engineering, Image blind deblurring, Noisy and blurry image, Bayesian statistics, double discrete wavelet transform, deblur with IMU, Motion estimation, Spatially varying blur
Copyright 2015, author
Zhang, Yi, "Blur image processing" (2015). Graduate Theses and Dissertations. 1063.