IMAGE COMPRESSION USING AFFINE FRACTAL INTERPOLATION ON RECTANGULAR LATTICES

Fractals ◽  
2006 ◽  
Vol 14 (04) ◽  
pp. 259-269 ◽  
Author(s):  
V. DRAKOPOULOS ◽  
P. BOUBOULIS ◽  
S. THEODORIDIS
Keyword(s):  
Image Compression ◽  
Analytical Study ◽  
Image Data ◽  
Fractal Interpolation ◽  
One Dimensional ◽  
Fractal Surfaces ◽  
Fractal Modeling ◽  
Interpolation Techniques ◽  
Rectangular Lattices

Two methods for representing discrete image data on rectangular lattices using fractal surfaces are proposed. They offer the advantage of a more general fractal modeling compared to previous one-dimensional fractal interpolation techniques resulting in higher compression ratios. Theory, implementation and analytical study of the proposed methods are also presented.

IMAGE COMPRESSION USING RECURRENT BIVARIATE FRACTAL INTERPOLATION SURFACES

2006 ◽  
Vol 16 (07) ◽  
pp. 2063-2071 ◽  
Author(s):  
P. BOUBOULIS ◽  
LEONI DALLA ◽  
V. DRAKOPOULOS
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Analytical Study ◽  
New Method ◽  
Fractal Interpolation ◽  
Affine Transformations ◽  
Fractal Modeling ◽  
Rectangular Lattices ◽  
Fractal Methods

A new method for constructing recurrent bivariate fractal interpolation surfaces through points sampled on rectangular lattices is proposed. This offers the advantage of a more flexible fractal modeling compared to previous fractal techniques that used affine transformations. The compression ratio for the above mentioned fractal scheme as applied to real images is higher than other fractal methods or JPEG, though not as high as JPEG2000. Theory, implementation and analytical study are also presented.

A controlled fractal interpolation method based on random midpoint displacement for coastline

GEOMATICA ◽  
2017 ◽  
Vol 71 (2) ◽  
pp. 89-99
Author(s):  
Baode Jiang ◽  
Dongqi Wei ◽  
Zhong Xie ◽  
Zhanlong Chen
Keyword(s):  
Spatial Data ◽  
Interpolation Method ◽  
Fractal Interpolation ◽  
Quality Requirements ◽  
One Dimensional ◽  
Fractal Characteristic ◽  
Fractal Interpolation Function ◽  
Proper Order ◽  
Fractal Characteristics ◽  
Original Scale

Coastline has different geographical bending characteristics in different coastal geomorphic regions. The existing fractal interpolation methods for coastline mostly focus on how to simulate its fractal characteristic but neglect the geographical bending characteristic. This study presents an improved controlled fractal inter polation method based on one-dimensional Random Midpoint Displacement (RMD) that aims to preserve both the bending characteristics and fractal characteristics of coastline. First, the coastline is divided into sev eral parts based on its bending characteristics, in order to conserve the geographical bending struc ture of the coastline and change the uncontrollable general fractal interpolation into a combination of sev er al piece-wise interpolation units. Second, the fractal interpolation function of one-dimensional RMD is used for each divided bending unit of the coastline, and the parameters of RMD function are restricted by the con straints of each unit bending characteristics. Third, the results of fractal interpolation of each unit are linked together in proper order to obtain the approximate coastline. The experiments show that this method can maintain the geographical bending characteristics and fractal characteristics of coastline, and when the ratio of target scale to the original scale is not more than 3 times, the accuracy of interpolation spatial coor di nates can meet the quality requirements of spatial data.

scholarly journals Image Compression Approach using Segmentation and Total Variation Regularization

2021 ◽  
Vol 15 ◽  
pp. 43-47
Author(s):  
Ahmad Shahin ◽  
Walid Moudani ◽  
Fadi Chakik
Keyword(s):  
Image Compression ◽  
Total Variation ◽  
Image Data ◽  
Smart Devices ◽  
Multimedia Content ◽  
Total Variation Regularization ◽  
Second Stage ◽  
Tv Regularization ◽  
Rof Model

In this paper we present a hybrid model for image compression based on segmentation and total variation regularization. The main motivation behind our approach is to offer decode image with immediate access to objects/features of interest. We are targeting high quality decoded image in order to be useful on smart devices, for analysis purpose, as well as for multimedia content-based description standards. The image is approximated as a set of uniform regions: The technique will assign well-defined members to homogenous regions in order to achieve image segmentation. The Adaptive fuzzy c-means (AFcM) is a guide to cluster image data. A second stage coding is applied using entropy coding to remove the whole image entropy redundancy. In the decompression phase, the reverse process is applied in which the decoded image suffers from missing details due to the coarse segmentation. For this reason, we suggest the application of total variation (TV) regularization, such as the Rudin-Osher-Fatemi (ROF) model, to enhance the quality of the coded image. Our experimental results had shown that ROF may increase the PSNR and hence offer better quality for a set of benchmark grayscale images.

scholarly journals Design and Development of a Very Large Scale Integrated Circuit Architecture for a Digital Image Compression and Realization on Field Programmable Gate Array

2020 ◽  
Vol 9 (3) ◽  
pp. 3510-3516
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Integrated Circuit ◽  
Large Scale ◽  
Image Data ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Research Challenges ◽  
High Compression ◽  
Image Pixels

The domain of image signal processing, image compression is the significant technique, which is mainly invented to reduce the redundancy of image data in order to able to transmit the image pixels with high quality resolution. The standard image compression techniques like losseless and lossy compression technique generates high compression ratio image with efficient storage and transmission requirement respectively. There are many image compression technique are available for example JPEG, DWT and DCT based compression algorithms which provides effective results in terms of high compression ratio with clear quality image transformation. But they have more computational complexities in terms of processing, encoding, energy consumption and hardware design. Thus, bringing out these challenges, the proposed paper considers the most prominent research papers and discuses FPGA architecture design and future scope in the state of art of image compression technique. The primary aim to investigate the research challenges toward VLSI designing and image compression. The core section of the proposed study includes three folds viz standard architecture designs, related work and open research challenges in the domain of image compression.

An Analytical Study of Cryosurgery in the Lung

1992 ◽  
Vol 114 (4) ◽  
pp. 467-472 ◽  
Author(s):  
J. C. Bischof ◽  
J. Bastacky ◽  
B. Rubinsky
Keyword(s):  
Finite Difference ◽  
Analytical Study ◽  
Outer Boundary ◽  
Temperature Profiles ◽  
One Dimensional ◽  
Thermal Phenomenon ◽  
Healthy Lung Tissue ◽  
Close Form ◽  
Finite Difference Techniques ◽  
Healthy Lung

The process of freezing in healthy lung tissue and in tumors in the lung during cryosurgery was modeled using one-dimensional close form techniques and finite difference techniques to determine the temperature profiles and the propagation of the freezing interface in the tissue. A thermal phenomenon was observed during freezing of lung tumors embedded in healthy tissue, (a) the freezing interface suddenly accelerates at the transition between the tumor and the healthy lung, (b) the frozen tumor temperature drops to low values once the freezing interface moves into the healthy lung, and (c) the outer boundary temperature has a point of sharp inflection corresponding to the time at which the tumor is completely frozen.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

scholarly journals Enhancement of Curve-Fitting Image Compression Using Hyperbolic Function

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 291 ◽  
Author(s):  
Walaa Khalaf ◽  
Dhafer Zaghar ◽  
Noor Hashim
Keyword(s):  
Image Compression ◽  
Curve Fitting ◽  
Image Data ◽  
Structural Similarity ◽  
Blocking Effect ◽  
Reconstructed Image ◽  
Hyperbolic Function ◽  
Image Size ◽  
Hyperbolic Tangent ◽  
Order Curve

Image compression is one of the most interesting fields of image processing that is used to reduce image size. 2D curve-fitting is a method that converts the image data (pixel values) to a set of mathematical equations that are used to represent the image. These equations have a fixed form with a few coefficients estimated from the image which has been divided into several blocks. Since the number of coefficients is lower than the original block pixel size, it can be used as a tool for image compression. In this paper, a new curve-fitting model has been proposed to be derived from the symmetric function (hyperbolic tangent) with only three coefficients. The main disadvantages of previous approaches were the additional errors and degradation of edges of the reconstructed image, as well as the blocking effect. To overcome this deficiency, it is proposed that this symmetric hyperbolic tangent (tanh) function be used instead of the classical 1st- and 2nd-order curve-fitting functions which are asymmetric for reformulating the blocks of the image. Depending on the symmetric property of hyperbolic tangent function, this will reduce the reconstruction error and improve fine details and texture of the reconstructed image. The results of this work have been tested and compared with 1st-order curve-fitting, and standard image compression (JPEG) methods. The main advantages of the proposed approach are: strengthening the edges of the image, removing the blocking effect, improving the Structural SIMilarity (SSIM) index, and increasing the Peak Signal-to-Noise Ratio (PSNR) up to 20 dB. Simulation results show that the proposed method has a significant improvement on the objective and subjective quality of the reconstructed image.

Intervalley kinetic energy terms in the effective mass equation: a one-dimensional analytical study

1989 ◽  
Vol 67 (9) ◽  
pp. 896-903 ◽  
Author(s):  
Lorenzo Resca
Keyword(s):  
Kinetic Energy ◽  
Effective Mass ◽  
Analytical Study ◽  
Three Dimensional ◽  
Real Space ◽  
The Other ◽  
Alternative Formulation ◽  
One Dimensional ◽  
Symmetry Properties ◽  
Band Case

We show that a one-dimensional analytical study allows us to test and clarify the derivation, assumptions, and symmetry properties of the intervalley effective mass equation (IVEME). In particular, we show that the IVEME is consistent with a two-band case, and is in fact exact for a model that satisfies exactly all its assumptions. On the other hand, an alternative formulation in k-space that includes intervalley kinetic energy terms is consistent with a one-band case, provided that intra-valley kinetic energy terms are also calculated consistent with one band. We also show that the standard symmetry assumptions for both real space and k-space formulations are not actually exact, but are consistent with a "total symmetric" projection, or with taking spherical averages in a three-dimensional case.

Pulsatile Flow Behavior in Elastic Systems Containing Wave Reflection Sites

1969 ◽  
Vol 91 (1) ◽  
pp. 95-102 ◽  
Author(s):  
J. L. Campbell ◽  
T. Yang
Keyword(s):  
Pulsatile Flow ◽  
Analytical Study ◽  
Wave Reflection ◽  
Flow Behavior ◽  
Reasonable Accuracy ◽  
One Dimensional ◽  
Test Conditions ◽  
Elastic Systems ◽  
Mass Flow Rates ◽  
Human Cardiovascular System

An analytical study is presented for one-dimensional, pulsatile flow of an incompressible fluid in systems of elastic tubing. Nonlinear terms are retained in the system of describing equations. Three experimental test systems with characteristics similar in some respects to those of the human cardiovascular system are described. These systems were used for experimental verification of the analytical predictions. Comparisons of the analytical predictions and experimental results show that pressures, mass flow rates, and velocities can be predicted with reasonable accuracy for all test conditions employed on the three models.

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