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53 Image and Video Restoration

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Digital images and video, acquired by still cameras, consumer camcorders, or even broadcast-quality video cameras, are usually degraded by some amount of blur and noise. | A. Murat Tekalp. Image and Video Restoration. 2000 CRC Press LLC. http www.engnetbase.com . Image and Video Restoration A. Murat Tekalp University of Rochester 53.1 Introduction 53.2 Modeling Intra-Frame Observation Model Multispectral Observation Model Multiframe Observation Model Regularization Models 53.3 Model Parameter Estimation Blur Identification Estimation of Regularization Parameters Estimation of the Noise Variance 53.4 Intra-Frame Restoration Basic Regularized Restoration Methods Restoration of Images Recorded by Nonlinear Sensors Restoration of Images Degraded by Random Blurs Adaptive Restoration for Ringing Reduction Blind Restoration Deconvolution Restoration of Multispectral Images Restoration of Space-Varying Blurred Images 53.5 Multiframe Restoration and Superresolution Multiframe Restoration Superresolution Superresolution with Space-Varying Restoration 53.6 Conclusion References 53.1 Introduction Digital images and video acquired by still cameras consumer camcorders or even broadcast-quality video cameras are usually degraded by some amount of blur and noise. In addition most electronic cameras have limited spatial resolution determined by the characteristics of the sensor array. Common causes of blur are out-of-focus relative motion and atmospheric turbulence. Noise sources include film grain thermal electronic and quantization noise. Further many image sensors and media have known nonlinear input-output characteristics which can be represented as point nonlinearities. The goal of image and video image sequence restoration is to estimate each image frame or field as it would appear without any degradations by first modeling the degradation process and then applying an inverse procedure. This is distinct from image enhancement techniques which are designed to manipulate an image in order to produce more pleasing results to an observer without making use of particular degradation models. On the other hand superresolution refers to estimating an .