The remarkable development of the medical imagery is due to the large use of telecommunications and information technologies in the medical domain. However, since the telemedicine is a medical act that must answer to stern rules, and follow the easiness that is offered by the informatics sciences to violate the confidentiality and authenticity of medical data. To resolve this problem, a lot of methods combining compression and encryption have been developed in the literature to secure the transmission and the storage of medical images. In this paper, we propose a new approach of partial encryption based on the Discrete Wavelet Transform (DWT) and compatible with the norm JPEG2000 in order to assure an optimal and a secure transmission and storage of medical images. This approach is, on one hand, faster since it permits a very important gain in the encryption-decryption processing time (only 6.25% of the DWT matrix coefficients will be encrypted), and on the other hand more efficient because it permits to get an encrypted medical image.

In this paper we propose a novel image encryption scheme. The proposed method is based on the chaos theory. Our cryptosystem uses the chaos theory to define a dynamic chaotic Look-Up Table (LUT) to compute the new value of the current pixel to cipher. Applying this process on each pixel of the plain image, we generate the encrypted image. The results of different experimental tests, such as Key space analysis, Information Entropy and Histogram analysis, show that the proposed encryption image scheme seems to be protected against various attacks. A comparison between the plain and encrypted image, in terms of correlation coefficient, proves that the plain image is very different from the encrypted one.

Despite their frequent use in our daily life, the expansion and reduction of images are among the least studied research areas in the literature. That is why the present research paper undertakes the study of the different techniques used for reducing and enlarging images, whose combination will be a new protocol (REPro) for the transmission of medical images. The proposed approach consists in reducing the image when sent and enlarging it when received, which allows for consumption saving of the bandwidth allocated to the diagnostics service. To do so, the performance of our new protocol was tested for the transfer of scars images (color images) and ultrasound images (grayscale images) in terms of the resemblance between the original image, on one hand, and the reduced and then enlarged one, on the other hand.

The image segmentation is one of the most used steps in image processing applications. Indeed, this process enables us to extract feature vectors which could be useful for experts decision and recognition task. This paper deals with the radar images segmentation for recognition targets. However, the radar images, generally include noise resulting from the acquisition step and from the several techniques of radar image reconstruction. In this work, we aimed to extract the general shape from the ISAR images. Accordingly, we combined two techniques: the Fisher algorithm and the watershed technique.