Embedding in medical images with contrast enhancement and tamper detection capability
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Embedding in medical images with contrast enhancement and tamper detection capability Shifa Showkat 1 & Shabir A. Parah 1
& Solihah Gull
1
Received: 23 May 2019 / Revised: 20 August 2020 / Accepted: 26 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
This paper presents an efficient data hiding technique capable of providing improved visual quality of watermarked images, besides having the ability to detect the tamper, if any. It is a spatial domain approach in which major emphasis is on improving the visual quality rather than increasing the PSNR or the embedding capacity. The medical images have been divided into Region of Interest (ROI) and Non-Region of Interest (NROI). Bringing out details that lie within the low dynamic range is very important in medical images for effective diagnosis. ROI being diagnostically critical region is enhanced using contrast stretching and subsequently, data is reversibly embedded into the peak bins of ROI. Only those peak bins are employed for reversible data embedding that have an adjacent empty bin to overcome the problem of overflow and underflow. In NROI, the uniform intensity and redundant information region, Least Significant Bit (LSB) embedding is employed for increasing the payload. For tamper detection, a fragile watermark has been embedded in the ROI. To evaluate the scheme various parameters like peak signal to noise ratio (PSNR), No-Reference Quality Metric for contrast-distorted images (NRCDIQA) and Structural Similarity Index Matrix (SSIM) have been calculated. The experimental results show a remarkable increase in visual quality compared to state-of-art. Keywords Reversible data hiding . Contrast stretching . Tamper detection . Medical image watermarking
1 Introduction With the accelerating digitization scenario and exceptionally increased connectivity, the total outlook of various technological fields has experienced remarkable changes. Internet of Things
* Shabir A. Parah [email protected]
1
Department of Electronics& Instrumentation Technology, University of Kashmir, J, and K, Srinagar 190006, India
Multimedia Tools and Applications
(IoT) has paved the way for excellent healthcare systems resulting in the emergence of ehealthcare with the principle objective being ‘personalization of healthcare’. The typical function of an e-healthcare setup includes continuous collection and monitoring of patientspecific data, analysis of the received data, and transmission of the processed information. DICOM (Digital Imaging and Communications in Medicine) is a standard used for transmission and storage of information in medical images. Digital imagery forms a critical part in ediagnosis and is very important for the transmission of Electronic Patient Record (EPR) in an e-health setup. One of the requirements of the healthcare industry is to store the medical records of patients which comprise medical images and their analysis. The different modalities in which medical images are generated and stored by medical imaging sys
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