Abstract
Steganalysis is the art of detecting the stego images from the clean image. In the past few years, steganographers are hiding the secret messages in the most significant areas of images such as edges, curves, and some other tricky undetectable areas of the image. The small distortion channel is framed that fruitfully detects the edges and textures of an image and also it visually similar that greatly serves as a bounding frame for embedding the hidden messages. To detect the stego images, formal steganalysis methods are available based on clean images. This proposed work introduces the curvelet transform with soft thresholding to denoise the images for exposing the stego content. Experimental results show that various denoising methods are compared with curvelet transforms, the performance measures are taken, and it clearly shows that curvelet denoising method is state of the art than the other denoising method.
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Hemalatha, J., Kavitha Devi, M.K., Geetha, S. (2019). Performance Analysis of Image Denoising with Curvelet Transform in Detecting the Stego Noise. In: Saini, H., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 32. Springer, Singapore. https://doi.org/10.1007/978-981-10-8201-6_50
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DOI: https://doi.org/10.1007/978-981-10-8201-6_50
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