Advance medical imaging requires storage of large quantities of digitized clinical data. Due to the bandwidth and storage limitations, medical images must be compressed before transmission and storage. Diagnosis is effective only when compression techniques preserve all the relevant and important image information needed. There are basically two types of image compression: lossless and lossy. L...

We studied two image characteristics, the smoothness and the similarity, which give rise to local and global redundancy in image representation. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. The similarity means that any patterns in an image repeat itself anywhere in the rest of the image. In this sense, we proposed a lossless medical ...

This paper proposes the implementation of an Enhanced Partial EZW algorithm that is based on the probability of significant coefficients within each bit plane on the lung X-ray image and thereby improves the performance. The main purpose of this paper is to analyse the impact and quality of wavelet filter for EZW and also to look into the effect of the level of wavelet decomposition towards com...

The amount of image data generated each day in health care is ever increasing, especially in combination with the improved scanning resolutions and the importance of volumetric image data sets. Handling these images raises the requirement for efficient compression, archival and transmission techniques. Currently, JPEG 2000's core coding system, defined in Part 1, is the default choice for medic...

The basic goal of region of interest (ROI) based compression for medical image is to enhance the compression efficiency for transmission and storage.Main goal of Region of interest(ROI) compression is to compressROI with supreme quality as compared to other region called Background. For an example, while compressing medical image the diagnostically important region should be compressed with bet...

Lossless compression techniques are essential in archival and communication of large amounts of homogeneous data in radiological image databases. This paper exploits dependencies that exist between the pixel intensities in three dimensions to improve compression for a set of similar medical images. These 3-D dependencies are systematically presented as histograms, plots of wavelet decomposition...

High resolution multidimensional image data yield huge datasets. For compression and analysis, 2D approaches are often used, neglecting the information coherence in higher dimensions, which can be exploited for improved compression. We designed a wavelet compression algorithm suited for data of arbitrary dimensions, and assessed its ability for compression of 4D medical images. Basically, separ...

Problem statement: Identifying the new lossless image compression algorithm for high performance applications like medical and satellite imaging; a high quality lossless image is most important when reproduction which leads to classify the data for decision making. Approach: A new lossless hybrid algorithm based on simple selective scan order with Bit Plane Slicing method is presented for lossl...

This paper focuses on the very important aspect of image compression and that too on the medical images which are very important so far as diagnosis of various dieses are concerned. This paper focuses on two major aspects i.e. compression on medical images so that the storage space and bandwidth can be saved and also keeping very important information for effective diagnosis. In this paper we h...