Interpolated Implicit Pixel-based Novel Hybrid Approach Towards Image Steganography

Abstract

Background: Steganography is the approach of camouflaging the covert object within another cover object. This manuscript suggested a novel steganography approach to conceal the covert data presence. The basic idea behind this is to generate an information-hiding approach that increases the payload capacity and good PSNR value without sacrificing much distortion of the image. Objectives: To develop a novel data-hiding approach that increases imperceptibility, robustness, and payload capacity. Methods: The Neighbour Mean Interpolation technique is used to scale up the original image to generate Interpolated pixels of the given image. An even-odd scheme on the interpolated stego pixel is used to camouflage the obscure code. MATLAB is used for the implementation of the new approach and results calculation. Results: The Experimental analysis reveals that our suggested approach has a finer embedding capacity for camouflaging the secret data as the original image of size (MxN) is scaled up to size (2M- 1 x2N-1) and also manages the good visuality of the cover or graven image. The proposed method is compared with Jung and Yoo, and Selvrani's method. The result of this comparison shows that the proposed method has finer imperceptibility than these two previously existing techniques. Conclusion: A novel approach towards image steganography using neighbor mean interpolation has been proposed and implemented. A new steganography method is used for camouflaging the confidential code into the cover object using NMI without producing any major differences in the input image. The new approach provides better imperceptibility, robustness, and payload capacity.