离散余弦变换
数字水印
离散小波变换
人工智能
块(置换群论)
感兴趣区域
峰值信噪比
计算机视觉
特征(语言学)
算法
相似性(几何)
噪音(视频)
模式识别(心理学)
计算机科学
图像(数学)
小波
医学
数学
小波变换
语言学
哲学
几何学
作者
Rajkumar Soundrapandiyan,Kannadasan Rajendiran,Arunkumar Gurunathan,Akila Victor,Ramani Selvanambi
标识
DOI:10.1117/1.jmi.11.1.014002
摘要
PurposeOver the past decade, the diagnostic information of the patients are digitally recorded and transferred. During the transmission of patients data, the security and authenticity of the information has to be ensured. Medical image watermarking technology has recently advanced because it can be used to conceal patient information while ensuring the authenticity. We propose a multiple watermarking method for securing clinical medical images.ApproachIn this watermarking method, the quality feature property and private label property information are embedded as watermarks in the original image. Initially, medical images are divided into the region of interest (ROI) and non-interest region (NIR). Second, a two-level discrete wavelet transform (DWT) is applied to the ROI and the coefficients LL1 (LL2, LH2, HL2, HH2), LH1, HL1, and HH1 are generated. Watermarks are embedded using the DWT low-frequency sub-band (LL2) by quantizing the low-frequency coefficients. Next, the NIR is separated into non-overlapping 8×8 blocks, and a discrete cosine transform (DCT) is applied for each block. The DCT coefficients of each block are sorted using the zigzag transform. For embedding, eight intermediate frequency coefficients are used. Finally, the feature information is embedded in the ROI, and the tag information is embedded in the NIR.ResultsThe performance of the DWT-DCT watermarking method is calculated using the metrics of peak signal-to-noise ratio (PSNR), structural similarity index measure, and mean square error. The proposed method obtained the better PSNR value of 45.76 dB.ConclusionsThe proposed model works well for clinical medical images when compared with the existing techniques.
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