Hybrid Median Filter for Noise Removal in Digital Images

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Hybrid Median Filter for Noise Removal in Digital Images
Images capture by the camera and processed and stored in memory. During this process the images are corrupted due to impulse noises. The image pixels are getting damaged due to these noises. The noise occurs due to transmission errors, malfunctioning pixel elements in the camera sensors, faulty memory locations, and timing errors in analog-to-digital conversion. Then our goal is to remove that type of noise in maximum amount by preserving the main image features. Image processing consists of many filters in order to remove the impulse noises.

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One of the filter is Hybrid median filter which is somewhat improved version of median filter, which removes the noise better than median filter. Image filters produce a new image from an original by operating on the pixel values. Filters are used to suppress noise, enhance contrast, find edges, and locate features. If we want to enhance the quality of images, we can use various filtering techniques which are available in image processing. There are various filters which can remove the noise from images and preserve image details and enhance the quality of image.


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The common noise which contains the image is impulse noise. The impulse noise is salt and pepper noise (image having the random black and white dots). Mean filter not perfect for remove impulse noise. Impulse noise can be removed by order statistics filter. The median filter is the filter removes most of the noise in image. But there is advanced filter called hybrid median filter which preserves corner with removal of impulse noise.

Kits required:

  1. Hybrid Median Filter
Who should do this project?
If you are interested in digital signal processing, then you should do this project to increase your knowledge database

Kit required to develop Hybrid Median Filter for Noise Removal in Digital Images:
Technologies you will learn by working on Hybrid Median Filter for Noise Removal in Digital Images:


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