Modeling nonstationary lens blur using eigen blur kernels for restoration
نویسندگان
چکیده
منابع مشابه
Modelling Lens Blur
Modelling the effect of corrective eye-wear’s can give optical designers and users an understanding of adopting a given lens design. Part of modelling the lenses is its effect on blur due to the eye’s inability to focus on every plane at once. Although the Gaussian convolution and depth-of-field algorithms are two existing methods to generate blurred images, neither are suitable for the lens mo...
متن کاملMotion Blur : Analysis and Restoration
Motion blur is a phenomenon which is corrupting images when, any motion occurs between the camera viewpoint and the captured scene during the acquisition. Rarely this can be described with a shift invariant operator although this is a common assumption in the literature. In a motion blurred image, the Point Spread Function (PSF) of each pixel is determined by the relative motion between the cam...
متن کاملBlur Identification Using Neural Network for Image Restoration
A prior knowledge about the distorting operator and its parameters is of crucial importance in blurred image restoration. In this paper the continuousvalued multilayer neural network based on multi-valued neurons (MLMVN) is exploited for identification of a type of blur among six trained blurs and of its parameters. This network has a number of specific properties and advantages. Its backpropag...
متن کاملType of Blur and Blur Parameters Identification Using Neural Network and Its Application to Image Restoration
The original solution of the blur and blur parameters identification problem is presented in this paper. A neural network based on multi-valued neurons is used for the blur and blur parameters identification. It is shown that using simple single-layered neural network it is possible to identify the type of the distorting operator. Four types of blur are considered: defocus, rectangular, motion ...
متن کاملImage Restoration Using Blur Invariants In Wavelet Transform
Image restoration is an important issue in high-level image processing. Images are often degraded during the data acquisition process. The degradation may involve blurring, information loss due to sampling, quantization effects, and various sources of noise. The purpose of image restoration is to estimate the original image from the degraded data. It is widely used in various fields of applicat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Optics Express
سال: 2020
ISSN: 1094-4087
DOI: 10.1364/oe.405448