Multiple watermarking on medical images using selective discrete wavelet transform coefficients - Singh A.K.; Kumar B.; Dave M.; Mohan A. (My University, 2025)
This paper presents a new spread-spectrum based secure multiple watermarking scheme on medical images in wavelet transform domain by using selective discrete wavelet transform (DWT) coefficients for embedding. The proposed algorithm is applied for embedding text watermarks like patient identification/source identification represented in binary arrays using ASCII code and doctor's signature or telemedicine centre name represented in binary image format into host digital radiological image for potential telemedicine applications. The algorithm is based on secure spread-spectrum technique where pseudo-noise (PN) sequences are generated corresponding to each watermarking bit and embedding of these sequences is done column wise into the selected DWT coefficients in the subband. Selection of DWT coefficient for embedding is done by thresholding the coefficient values present in that column. In the embedding process, the cover image is decomposed at second level DWT. The image and text watermark is embedded into the selective coefficients of the first level and second level DWT respectively. In order to enhance the robustness of text watermarks like patient identity code, error correcting code (ECC) is applied to the ASCII representation of the text watermark before embedding. Results are obtained by varying the gain factor, subband decomposition levels, size of watermark, and medical image modalities. Performace of the proposed watermarking algorithm is analyzed against numerous known attacks like compression, filtering, noise, sharpening, scaling and histogram equalization and desired outcome is obtained without much degradation in extracted watermarks and watermarked image quality. The method is compared with other reported techniques and has been found to be giving superior performance for robustness and imperceptibility suggested by other authors. Copyright © 2015 American Scientific Publishers.