Encrypted Image Denoising using Adaptive Weighted Median Filter

Background /Objectives: A novel approach for image encryption using chaotic functions and for denoising encrypted image using adaptive weighted median filter is proposed. The proposed method is implemented for encryption and quality improvement of biometric images. Methods/Statistical Analysis: The proposed techniques are simulated using MATLAB platform. Qualitative and quantitative statistical analyses have been done using performance parameters such as Peak Signal to Noise Ratio, Mean Square Error, and Structural Similarity Index. Denoising of biometric images is computed based on these performance parameters. Findings: Experimental computation of proposed algorithm shows how a high peak signal to noise ratio, low mean square error and comparable structural similarity index infers the effectiveness of chaotic algorithm for image encryption. Further denoising procedure using adaptive weighted median filter is utilized for further enhancing and improving biometric image quality while suppressing noise present in the image.Application/Improvements: The proposed method for image encryption and denoising of biometric image provides a secure way for encryption and relatively effective image quality improvement as compared to existing models.