False Alarm Based Quasi Periodic Noise Removal in Digital Images
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 1
Abstract
In general noise is random is nature and can be removed using both static and adaptive filters. Images may be affected by quasi-periodic noise. This artefact is often caused by electrical interferences during image acquisition or transmission, which makes remote sensing applications especially prone to the phenomenon. Periodic noise gives more or less sharp spikes in the image spectrum, which can be filtered out using notch filters. The difficulty is to automate spike detection, that is, notch filter design. Some authors suggest detecting spikes in the Fourier domain as large deviations with respect to a localized median value. However, distinguishing between spikes caused by a localized texture or a repetitive structure (common in man-made environments) and spurious ones caused by periodic noise is still challenging. It has been observed in past that periodic noise is likely to be the only periodic structure present in any patch extracted from the impaired image. The quasi periodic noise changes in structure over the time, thus removal becomes more complex. In this work, an algorithm is detailed for the design of notch filter, which is capable of suppressing quasi periodic noise.
Authors and Affiliations
Swati Srivastava, Akash Awasthi
Keywords
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