scholarly journals Pyramid based Progressive Transmission System with Hybrid Compression Scheme for Medical Images

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
H. K. Ravikiran ◽  
J. Jayanth
Keyword(s):  
Medical Images ◽  
Transmission System ◽  
Progressive Transmission ◽  
Compression Scheme

The Kolmogorov Spline Network for Image Processing

2013 ◽  
pp. 54-78
Author(s):  
Pierre-Emmanuel Leni ◽  
Yohan D. Fougerolle ◽  
Frédéric Truchetet
Keyword(s):  
Image Processing ◽  
Progressive Transmission ◽  
Original Image ◽  
Jpeg 2000 ◽  
Compression Scheme ◽  
Construction Methods ◽  
Reconstruction Quality ◽  
Univariate Function ◽  
Univariate Functions ◽  
Image Pixels

In 1900, Hilbert stated that high order equations cannot be solved by sums and compositions of bivariate functions. In 1957, Kolmogorov proved this hypothesis wrong and presented his superposition theorem (KST) that allowed for writing every multivariate functions as sums and compositions of univariate functions. Sprecher has proposed in (Sprecher, 1996) and (Sprecher, 1997) an algorithm for exact univariate function reconstruction. Sprecher explicitly describes construction methods for univariate functions and introduces fundamental notions for the theorem comprehension (such as tilage). Köppen has presented applications of this algorithm to image processing in (Köppen, 2002) and (Köppen & Yoshida, 2005). The lack of flexibility of this scheme has been pointed out and another solution which approximates the univariate functions has been considered. More specifically, it has led us to consider Igelnik and Parikh’s approach, known as the KSN which offers several perspectives of modification of the univariate functions as well as their construction. This chapter will focus on the presentation of Igelnik and Parikh’s Kolmogorov Spline Network (KSN) for image processing and detail two applications: image compression and progressive transmission. Precisely, the developments presented in this chapter include: (1)Compression: the authors study the reconstruction quality using univariate functions containing only a fraction of the original image pixels. To improve the reconstruction quality, they apply this decomposition on images of details obtained by wavelet decomposition. The authors combine this approach into the JPEG 2000 encoder, and show that the obtained results improve JPEG 2000 compression scheme, even at low bitrates. (2)Progressive Transmission: the authors propose to modify the generation of the KSN. The image is decomposed into univariate functions that can be transmitted one after the other to add new data to the previously transmitted functions, which allows to progressively and exactly reconstruct the original image. They evaluate the transmission robustness and provide the results of the simulation of a transmission over packet-loss channels.

Region-of-interest-based wavelet compression scheme for medical images

1997 ◽  
Author(s):  
Dongkyoo Shin ◽  
Hsien-Hsun S. Wu ◽  
Jyh-Charn S. Liu
Keyword(s):  
Medical Images ◽  
Region Of Interest ◽  
Compression Scheme ◽  
Wavelet Compression

scholarly journals Joint source–channel coding: Secured and progressive transmission of compressed medical images on the Internet

2008 ◽  
Vol 32 (4) ◽  
pp. 258-269 ◽  
Author(s):  
Marie Babel ◽  
Benoît Parrein ◽  
Olivier Déforges ◽  
Nicolas Normand ◽  
Jean-Pierre Guédon ◽  
...  
Keyword(s):  
Channel Coding ◽  
Medical Images ◽  
The Internet ◽  
Progressive Transmission ◽  
Joint Source Channel Coding ◽  
Source Channel Coding

scholarly journals A HYBRID COMPRESSION MODEL FOR CLUSTERS OF SIMILAR MEDICAL IMAGES

2003 ◽  
Vol 15 (01) ◽  
pp. 38-45
Author(s):  
JIANN-DER LEE ◽  
SHU-YEN WAN ◽  
RUI-FENG WU
Keyword(s):  
Region Growing ◽  
Original Data ◽  
Experimental Results ◽  
Progressive Transmission ◽  
Compression Scheme ◽  
Centroid Method ◽  
Compression Efficiency ◽  
Compression Model ◽  
Similar Images ◽  
The Difference

In this paper, a new compression scheme called hybrid compression model (HCM) is proposed for compressing clusters of similar images. The HCM exploits region growing to segment the median image that created by a cluster of similar images; and further, it uses centroid method to predict the values of original images data. The difference between the predict values and original data is stored for later use of progressive transmission. The experimental results obtained on various images show that our method provides significant improvement in compression efficiency while compared to the traditional centroid method.

scholarly journals A Combined Encryption Compression Scheme Using Chaotic Maps

2013 ◽  
Vol 13 (2) ◽  
pp. 75-81 ◽  
Author(s):  
Bhagwati Prasad ◽  
Kunti Mishra
Keyword(s):  
Chaotic Maps ◽  
Medical Images ◽  
Real Life ◽  
Galois Field ◽  
Compression Scheme ◽  
Encrypted Data ◽  
Legal Documents ◽  
High Security ◽  
Significant Compression ◽  
Multiple Chaotic Maps

Abstract The intent of this paper is to propose an encryption compression scheme using multiple chaotic maps along with the concept of Galois field. This method improves the security of the encrypted data and a significant compression is also achieved. The obtained high security architectures are ideal for many real life applications such as medical images, legal documents and military and other operation

Content-driven pyramid compression of medical images for error-free archival and progressive transmission

1995 ◽  
Vol 6 (3) ◽  
pp. 301-310 ◽  
Author(s):  
Franco Lotti ◽  
Bruno Aiazzi ◽  
Stefano Baronti ◽  
Andrea Casini ◽  
Luciano Alparone
Keyword(s):  
Medical Images ◽  
Progressive Transmission

An efficient compression scheme for 4-D medical images using hierarchical vector quantization and motion compensation

2011 ◽  
Vol 41 (9) ◽  
pp. 843-856 ◽  
Author(s):  
Binh P. Nguyen ◽  
Chee-Kong Chui ◽  
Sim-Heng Ong ◽  
Stephen Chang
Keyword(s):  
Vector Quantization ◽  
Motion Compensation ◽  
Medical Images ◽  
Compression Scheme
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