Digital Color Image required large amount of space to store and large bandwidth to transmit it. Due to limitations in bandwidth and in storage space, it is vital requirement to compresses digital color image. Color image compression is required with negligible loss in image quality for the effective use of further restored image. To meet this, numerous image compression techniques are developed in last several years. This paper analyses these techniques and presents a compression among them to find out the best method for digital color image compression. The objective of this paper is also to find out the best approach for developing new way of digital color image compression with minimum loss in image quality.
Existing methods to calculate the sound transmission loss (STL) of multilayered/patterned partitions require either fabrication of the partition and-time consuming experimental testing or computationally expensive numerical methodologies. This paper presents two fast and accurate methodologies developed using FEM and wave propagation theory to predict the STL curve for any geometrical/material configuration partition. In the first methodology, a FEM program calculates the frequency-dependant bending and shear-wave velocities of any configuration partition by performing a modal analysis on a two-dimensional cross section of the partition. The critical frequency of that partition is then obtained by calculating the frequency at which the wave-speed curve intersects the curve for speed of sound in air. In the second methodology, the critical frequency of the partition is used to obtain an equivalent homogeneous isotropic panel. The separation impedance (mass + bending + shear-wave impedances) of this equivalent panel is calculated to plot the STL curve, which can be considered as that of the original partition as they have similar wave dynamics and critical frequency. The model is experimentally and theoretically validated by comparing a sample of the results with several validated theoretical and experimental trends previously published in open literature.
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