An efficient enhanced medicinal leaf image production using Adaptive Gamma Correction Weighting Distribution (AGCWD) algorithm with guided filter

Abstract

The quality of an image is always degraded by the random variation called noise which is included in the contrast, intensity and other properties like brightness. Noise is added with an image during the digital image transmission. The image sensors are always affected by the normal physical environment factors like temperature, scanner dust particles and the parametric characteristics of the lens and the camera. Noise removal is important in the image transmission because any interference in the transmission channel can include noise into it. A medicinal plant leaf needs to be disease free for a harmless medicine production. It becomes a necessity for a method to produce a more contrast enhanced image with the efficient noise removal mechanism. The paper proposes a combinational approach of an Adaptive Gamma Correction Weighting Distribution (AGCWD) which mainly serves to enhance the contrast of the image and the Noise removal mechanism which is performed by a guided filter. The proposed method evaluated various performance metrics like Mean square error (MSE), Image enhancement factor (IEF), Peak Signal to noise Ratio (PSNR) And Mean Absolute Error (MAE). The evaluation of the proposed system gave more better performance results than while using the existent Bilateral filter.