Satellite Image Compression using Hybrid Transform Model
P Prema *, Dr. V.V. Ramalingam**
* Research Scholar, ** Associate Professor, SRM Institute of Science and Technology, KTR Campus
OBJECTIVE
⮚ To reduce insignificant information for efficient image
transmission..
⮚ To achieve higher compression ratios while maintaining
reconstructed image quality
ABSTRACT
⮚ Image compression is a strategy that uses fewer bits to
reduce the storage and memory requirements of an input
image.
⮚ Image compression is a critical methodology for reducing
insignificant information for efficient image transmission.
⮚ This paper proposes a multidimensional hybrid algorithm
that combines Discrete Wavelet Transform (DWT), Run-
Length Encoding (RLE), and Arithmetic Coding (AC) to
achieve higher compression ratios while maintaining
reconstructed image quality. A comparison of existing
approaches with the proposed method is performed.
CONCLUSION
⮚ The images have been wavelet
decomposed using three levels
and then subjected to Run-Length
Encoding. As the remote sensing
images have a number of similar
pixels, these stream of values are
replaced by a single value with its
count value. The encoded values
are then Arithmetic coded to
obtain a single-floating value to
achieve higher compression ratios
and PSNR values. The proposed
multifaceted hybrid methodology
comprising of DWT+RLE+AE
procures an average CR of 4.72
and PSNR of 46.84..
FUTURE WORK
⮚ To apply different earth
observation datasets to the
algorithms and evaluate the
performance.
PROPOSED SYSTEM
⮚ The methodology proposed to
establish satellite Image
Compression using Hybrid
Transform Model