High-resolution digital images that are used in geo-spatial and remote sensing technologies tend to be of large sizes, especially with newer satellite imageries that provide better than 5 m spatial resolution, and thereby consuming large storage space, large transmission bandwidth, and long transmission times. Therefore, method of compressing the archived images is required before storage and t...

Technically, all image data compression schemes can be categorized into two groups as lossless (reversible) and lossy (irreversible). Although some information is lost in the lossy compression, especially for the radiologic image compression, new algorithms can be designed to minimize the effect of data loss on the diagnostic features of the images. Wavelet transform (WT) constitute a new compr...

It is straightforward to apply general schemes for authenticating digital data to the problem of authenticating digital images. However, such a scheme would not authenticate images that have undergone lossy compression, even though they may not have been manipulated otherwise. In this paper we propose a scheme for authenticating the visual content of digital images. This scheme is robust to com...

In this work, we present a new content-based watermarking approach that uses geometric warping to embed watermarks with high robustness to strong lossy compression. The issue of hard decisions related to content-based watermarking is discussed and it is explained why hard decisions can involve bit errors in the watermark extraction process. This work contains a solution to prevent hard decision...

Lossless image compression has often employed techniques quite separate from those used for text compression or lossy image compression; most standards today employ modelling followed by coding (e.g. the JBIG standard, the IBM Q-coder, CCITT Group 4). Constantinescu and Storer present a lossy image compression scheme that can be viewed as a generalization of lossless dynamic dictionary compress...

Fractal image compression has been developed in the last decades using different approaches such as cosine transforms and neural nets. The common objective is to reduce the size of an input image while maintain an acceptable quality of the reconstructed after decompression. In fact, a lossy algorithm is always applied in order to gain high compression ratios compared to lossless techniques. In ...

Images are an important form of data and are used in almost every application. Some applications cannot use images directly due to the large amount of memory space needed to store these images. Image compression is to reduce irrelevance and redundancy of the image data in order to be able to store or transmit data in an efficient form. Compression of images plays an important role in storing th...

The high quality of the image produced by CT scan and MRI techniques is required to be maintained in order to avoid wrong diagnosis along with reduced file size. A lossless compression technique retains the image quality but achieves low to moderate compression ratio. Lossy compression, on the other hand, provides higher compression at the cost of degraded image quality. Thus there is need of i...

This paper describes a set of novel steganographic methods to secretly embed robust labels into image data for identifying image copyright holder and original distributor in digital networked environment. The embedded label is undetectable, unremovable and unalterable. Furthermore it can survive processing which does not seriously reduce the quality of the image, such as lossy image compression...