Variable Exponent, Linear Growth Functionals in Image Restoration
نویسندگان
چکیده
Abstract. We study a functional with variable exponent, 1 ≤ p(x) ≤ 2, which provides a model for image denoising, enhancement, and restoration. The diffusion resulting from the proposed model is a combination of total variation (TV)-based regularization and Gaussian smoothing. The existence, uniqueness, and long-time behavior of the proposed model are established. Experimental results illustrate the effectiveness of the model in image restoration.
منابع مشابه
Critical variable exponent functionals in image restoration
We study a variable exponent model for image restoration in the case that the exponent attains the critical value one. We prove existence and Γ-convergence. The results answer an open question by Li, Li and Pi [Variable exponent functionals in image restoration, Appl. Math. Comput. 216 (2010), no. 3, 870–882].
متن کاملImage Restoration by Variable Splitting based on Total Variant Regularizer
The aim of image restoration is to obtain a higher quality desired image from a degraded image. In this strategy, an image inpainting method fills the degraded or lost area of the image by appropriate information. This is performed in such a way so that the obtained image is undistinguishable for a casual person who is unfamiliar with the original image. In this paper, different images are degr...
متن کاملAdaptive data-driven regularization for variational image restoration in the BV space
We present a novel variational regularization in the space of functions of Bounded Variation (BV) for adaptive data-driven image restoration. The discontinuities are important features in image processing. The BV space is well adapted for the measure of gradient and discontinuities. More over, the degradation of images includes not only random noises but also multiplicative, spatial degradation...
متن کاملPerceptual regularization functionals for natural image restoration
Regularization constraints are necessary in inverse problems such as image restoration, optical flow computation or shape from shading to avoid the singularities in the solution. Conventional regularization techniques are based on some a priori knowledge of the solution: usually, the solution is assumed to be smooth according to simple statistical image or motion models. Using the fact that hum...
متن کاملBV and dual of BV image decomposition models and minimization algorithms
We propose in this paper minimization algorithms for image restoration using dual functionals and dual norms. In order to extract a clean image u from a degraded version f = Ku+ n, where f is the observation, K is a blurring operator and n represents additive noise, we impose a standard regularization penalty Φ(u) = ∫ φ(|∇u|)dx < ∞ on u, where φ is positive, increasing and has at most linear gr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- SIAM Journal of Applied Mathematics
دوره 66 شماره
صفحات -
تاریخ انتشار 2006