Create README.md

Author: rudrajit1729

Image_Processing/src/Filters/src/median_filter/README.md

@@ -0,0 +1,36 @@
+# Median Filtering on Image(SMF)
+Median Filtering is a neighborhood filtering technique used in order to remove noise from images and enhance its quality.
+
+Often during Image capturing and acquisition(specially in medical images) the image is disturbed by Salt and Pepper Noise(SPN)[Original pixel replaced by either maximum intenstiy pixel
+or minimum intensity pixel] which mainly occurs due to certain faults in sensors
+while capturing the image. Having noise in image makes it difficult for Computer Aided Detection(CAD). Nowadays, many Machine Learning and Deep Learning techniques are being applied on 
+medical images for computer aided diagnosis to reduce human error. Image Preprocessing is an important stage before the image can be fed to the model. Not restricting to that itself,
+Image Enhancement plays an important role in improving the quality of images and removing errors/noises from them.
+
+## Algorithm 
+The main idea of the median filter is to run through the signal entry by entry, replacing each entry with the median of neighboring entries. 
+The pattern of neighbors is called the "window", which slides, entry by entry, over the entire signal. For one-dimensional signals, the most obvious window is just the
+first few preceding and following entries, whereas for two-dimensional (or higher-dimensional) data the window 
+must include all entries within a given radius or ellipsoidal region (i.e. the median filter is not a separable filter).
+
+In Median filtering the edge detection becomes a bit difficult but that again is improved as we switch to fuzzy removal of noise. Median Filter is the most commonly used filter
+just for the fact that it is computationally faster than other existing techniques.
+
+## Metric Calculation
+The popular metrics for judging the quality of enhancement technique are - RMSE, PSNR, SSIM, & IEF. 
+
+These are statistical measures that judge the quality of output relying on data and mathematics. 
+
+Check on the links to have a brief idea about the concepts. In *Median_Filter.c* these concepts are applied for images where each pixel acts as a data point.
+
+1. Root Mean Squared Error(RMSE) - [Click To Know More](https://en.wikipedia.org/wiki/Root-mean-square_deviation)
+
+2. Peak Signal to Noise Ratio(PSNR) - [Click To Know More](https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio)
+
+3. Structural Similarity(SSIM) - [Click To Know More](https://en.wikipedia.org/wiki/Structural_similarity)
+
+4. Image Enhancement Factor(IEF) - [Click To Know More](https://in.mathworks.com/matlabcentral/answers/450377-how-to-calculate-enhancement-factor-for-an-image)
+
+## Results
+The SMF technique is used for removal of Salt and Pepper Noise but works well with other noises as well. SMF works well for upto 60% noise percentage. Above that it fails, new algorithms such as
+fuzzy median technique, Adaptive Weighted Mean Filtering technique and a lot more have been introduced as an add on of this algorithm and that works upto 85% noise.