DICOM image size reduction and data embedding using randomization technique

TLDR: This investigation mainly focuses on computing the data hiding capacity, Compression Ratio, Mean Square Error (MSE) and Peak to Signal Noise Ratio (PSNR) of medical images.

Abstract: With the development of Internet technologies, digital media can be transmitted conveniently over the Internet. However, medical information transmissions over the Internet still have to face all kinds of problem such as network bandwidth, integrity of data, image quality and security. Normally Medical images are in DICOM (Digital Imagine in Communication and Medicine) format. The DICOM technology is suitable when sending images between different departments within hospitals or/and other hospitals, and consultant. However, the header file to DICOM image adds additional size to the image. We have proposed new techniques of transforming DICOM format in to BMP(Bitmap Image file) format and divide data into two parts and embedding a patient data in an image in odd, number memory location of image pixel values. Fix length Huffman compression is applied to get lossless compressed image. This investigation mainly focuses on computing the data hiding capacity, Compression Ratio, Mean Square Error (MSE) and Peak to Signal Noise Ratio (PSNR) of medical images.