We propose a new image multiresolution transform that is suited for both lossless reversible and lossy compression The new transformation is similar to the subband decomposition but can be computed with only integer addition and bit shift operations During its calculation the number of bits required to represent the transformed image is kept small through careful scaling and truncations Numeric...

Digital imaging has had an enormous impact on scientific and industrial applications. Uncompressed images require considerable storage capacity and transmission bandwidth. The solution to this problem is to compress an image for desired application. There are two different compression categories : lossless and lossy . Lossless compression preserves the information in the image. Thus an image co...

In this chapter we describe methods how to compress spectral imaging data. Normally the spectral data is presented as spectral images which can be considered as generalizations of colour images. Rapid technological development in spectral imaging devices has initiated the need for the compression of raw data. Spectral imaging has been central to many remote sensing applications like geology and...

We propose a new image multiresolution transform that is suited for both lossless (reversible) and lossy compression. The new transformation is similar to the subband decomposition, but can be computed with only integer addition and bit-shift operations. During its calculation, the number of bits required to represent the transformed image is kept small through careful scaling and truncations. ...

With the increasing use of multimedia technologies, image compression requires higher performance as well as new features. To address this need in the specific area of still image encoding, a new standard is currently being developed, the JPEG2000. It is not only intended to provide rate-distortion and subjective image quality performance superior to existing standards, but also to provide feat...

This paper mainly address the image compression by using Principal component analysis (PCA) and JPEG. Image compression is the method of converting data file into smaller compact files for efficiency of storage and transmission. The main objective of compression of image is to reduce redundancy of bits in the image in order to store and transmit data in an effective way. Image compression techn...

Selective compression of a medical image (MI) becomes an important task in fields of diagnosis, in solving archiving, and transmission problems. In this paper, a proposed bichannel automatic compression technique for medical image processing (MIP) with ROI is introduced using two approaches. The first approach uses two different compression schemes (lossless and lossy) for inside and outside of...

Image compression helps in storing the transmitted data in proficient way by decreasing its redundancy. This technique helps in transferring more digital or multimedia data over internet as it increases the storage space. It is important to maintain the image quality even if it is compressed to certain extent. Depend upon this the image compression is classified into two categories : lossy and ...

The complementary paradigms of text compression and image compression suggest that there may be potential for applying methods developed for one domain to the other. In image coding, lossy techniques yield compression factors that are vastly superior to those of the best lossless schemes, and we show that this is also the case for text. This paper investigates the resulting tradeoff between sub...

In this paper, we present an image compression scheme based on the automatic segmentation of regions of interest (RoI) and a lossy wavelet compression algorithm adapted to this segmentation. Quasi-lossless compression is applied to the RoI while lossy compression is allowed outside the RoI, preserving at best the visual quality of the decoded image within a deened RoI. In fact, for diagnostic a...