This paper mentions how morphological component analysis, deep learning, and
steganography could be used to safeguard the dissemination, recognition, and affirmation of …

This work's primary goal is to secure the transmission of text hidden within the cover image
using steganography over a public network of computers. Steganography is a powerful tool …

A potential to extract detailed textual image texture features is a key characteristic of the
suggested approach, instead of using a single spatial texture feature. For the generation of …

In the era of modern medical imaging communal, huge volume of medical image data are
being acquired and need to be transmitted and archived which necessitate the development …

The large volume and complexity of medical imaging datasets are bottlenecks for storage,
transmission, and processing. To tackle these challenges, the application of low-rank matrix …

Digital medical images have become a vital resource that supports decision-making and
treatment procedures in healthcare facilities. The medical image consumes large sizes of …

The computerization of images have been important for different medical applications.
Nevertheless, the huge volume of medical images can rapidly saturate transmission …

Many classes of images contain spatial regions which are more important than other
regions. Compression methods capable of delivering higher reconstruction quality for …

We present a novel 3-D scalable compression method for medical images with optimized
volume of interest (VOI) coding. The method is presented within the framework of interactive …

JPEG-based compression is the most widely used image compression algorithm.
Previously, JPEG-XT-based work focused on 16-bit depth high-dynamic satellite infrared …