Watermark Compression in Digital Medical Image Watermarking

• Main Authors: Badshah, Gran, Liew, Siau-Chuin, Jasni, Mohamad Zain, Syifak Izhar, Hisham
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/5741/1/ICT-004.pdf; http://umpir.ump.edu.my/id/eprint/5741/
• Institution: Universiti Malaysia Pahang

Large size data not only require more storage space but also require more transmission time in communication environment. Mostly this obstacle exists in every type image communication process such as in satellite and distributed health facilities provision applications. Data compression causes reduction in storage space and communication time. Data compression is divided into two main categories, lossy and lossless. Although in lossy compression the compression ratio is higher than lossless but mostly important part of data is lost. During data lossless compression important data is not lost and only size reduction taking place. Teleradiology is a health promoting technology used to share medical images among different experts located apart from each other to analyze the image data for patient better treatment and surgical planning. Medical image data is very sensitive data and need its compression without any loss otherwise it will result in erroneous input into health recovery process. This paper focuses on Ultrasound medical image lossless compression using different techniques. PNG, GIF, JPG, JPEG2000 version j2c, JPEG2000 version jp2 in lossless mode techniques were used for this purpose as shown in table 1. The techniques were compared based on compression ratio, time taken during compression and PNG was found the best one. The selected technique is suggested to be used for digital watermarking of Ultrasound medical images. Our consideration is US images because US images are small in sizes as compared to images produced by other modalities and most of information is located in the central part of the image known as Region of Interest (ROI). The rest of the image other than ROI is known as Region of Non Interest (RONI). The main purpose of image compression is the removal of redundant data in such a way that it can be reversed to their original version for the desired operations [Vilas H. Gaidhane et al, 2011].