Abstract
We propose dual-domain filtering, an image processing paradigm that couples spatial domain with frequency domain filtering. Our dual-domain defined filter removes artifacts like residual noise of other image denoising methods and compression artifacts. Moreover, iterating the filter achieves state-of-the-art image denoising results, but with a much simpler algorithm than competing approaches. The simplicity and versatility of the dual-domain filter makes it an attractive tool for image processing.
Highlights
IntroductionImages may be degraded by additive white Gaussian noise, by arbitrary method noise, or by compression artifacts
Image enhancement and reconstruction are important tasks in image processing
We have introduced dual-domain filtering (DDF), a generalization of the spatial bilateral filter (BF) by including a frequency domain filter
Summary
Images may be degraded by additive white Gaussian noise, by arbitrary method noise, or by compression artifacts. To improve such images, specialized tools are often developed for each type of degradation. The bilateral filter (BF) [32] and its variant, the joint-bilateral filter [27], have become popular tools due to their simplicity and effectiveness in removing named artifacts. Bilateral filtering can be used for denoising images contaminated with weak noise or for removing unwanted details. Adaptive bilateral filtering has been proven effective for JPEG deblocking, as proposed by Zhang and Gunturk [36] and Nath, Hazarika, and Mahanta [25]
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