The Effect of Re-Use of Lossy JPEG Compression Algorithm on the Quality of Satellite Image

Hameed M Abduljabbar; Inbthaq Mohammed Ali Abdul Ameer Abdul Ameer

doi:10.14704/nq.2020.18.5.NQ20162

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Publication Date

Sat May 30 2020

Journal Name

Neuroquantology Journal

Volume

18

Issue Number

5

DOI

10.14704/nq.2020.18.5.NQ20162

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The Effect of Re-Use of Lossy JPEG Compression Algorithm on the Quality of Satellite Image

2D Scatter Plot

Signal-to-noise Ratio

Global Coefficient of Variation

Compression Ratio

Global Quartile Coefficient of Dispersion

Hameed M Abduljabbar

Inbthaq Mohammed Ali Abdul Ameer Abdul Ameer

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In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.

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Publication Date

Sun Nov 01 2020

Journal Name

Iop Conference Series: Materials Science And Engineering

Developed JPEG Algorithm Applied in Image Compression

Abdullah A.

Ghadah K.

Mohammed M.

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Abstract<p>JPEG is most popular image compression and encoding, this technique is widely used in many applications (images, videos and 3D animations). Meanwhile, researchers are very interested to develop this massive technique to compress images at higher compression ratios with keeping image quality as much as possible. For this reason in this paper we introduce a developed JPEG based on fast DCT and removed most of zeros and keeps their positions in a transformed block. Additionally, arithmetic coding applied rather than Huffman coding. The results showed up, the proposed developed JPEG algorithm has better image quality than traditional JPEG techniques.</p>

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(6)

Publication Date

Fri Apr 01 2016

Journal Name

Iosr Journal Of Computer Engineering

Lossless and Lossy Polynomial Image Compression

Ghadah

Maha A.

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(1)

Publication Date

Fri Apr 01 2016

Journal Name

Iosr Journal Of Computer Engineering

Lossless and Lossy Polynomial Image Compression

Ghadah

Maha A.

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(1)

Publication Date

Tue Aug 10 2021

Journal Name

Design Engineering

Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri

Image compression

Convolutional Autoencoder (CAE)

k-mean algorithm

PSNR

Compression Rate (CR)

MSE

Clustering

CLIC

Kodak

deep learning

lossy

Mohammed S. H.

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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Publication Date

Sun Jul 25 2021

Journal Name

Journal Of Al-qadisiyah For Computer Science And Mathematics

A Survey paper on Lossy Audio Compression Methods

compression types

audio compression

speech compression

lossy type

Zinah

Zainab J.

Anwar

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During the two last decades ago, audio compression becomes the topic of many types of research due to the importance of this field which reflecting on the storage capacity and the transmission requirement. The rapid development of the computer industry increases the demand for audio data with high quality and accordingly, there is great importance for the development of audio compression technologies, lossy and lossless are the two categories of compression. This paper aims to review the techniques of the lossy audio compression methods, summarize the importance and the uses of each method.

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Publication Date

Thu Jun 01 2017

Journal Name

Iosr Journal Of Computer Engineering

Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding

dr. Ghadah

rafaa Ismael

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Publication Date

Mon Mar 20 2023

Journal Name

2023 International Conference On Information Technology, Applied Mathematics And Statistics (icitams)

Hybrid Color Image Compression Using Signals Decomposition with Lossy and Lossless Coding Schemes

Hala

Loay E.

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Publication Date

Wed Dec 01 2021

Journal Name

Journal Of Physics: Conference Series

Art Image Compression Based on Lossless LZW Hashing Ciphering Algorithm

Sajaa G.

Safa S.

Faisel G.

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Abstract<p>Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and </p> ... Show More

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(2)

Publication Date

Thu Feb 07 2019

Journal Name

Journal Of The College Of Education For Women

EFFICIENCY SPIHT IN COMPRESSION AND QUALITY OF IMAGE

Asst. Lecturer Enas M.

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Image compression is an important tool to reduce the bandwidth and storage
requirements of practical image systems. To reduce the increasing demand of storage
space and transmission time compression techniques are the need of the day. Discrete
time wavelet transforms based image codec using Set Partitioning In Hierarchical
Trees (SPIHT) is implemented in this paper. Mean Square Error (MSE), Peak Signal
to Noise Ratio (PSNR) and Maximum Difference (MD) are used to measure the
picture quality of reconstructed image. MSE and PSNR are the most common picture
quality measures. Different kinds of test images are assessed in this work with
different compression ratios. The results show the high efficiency of SPIHT algori

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Publication Date

Wed May 17 2017

Journal Name

Ibn Al-haitham Journal For Pure And Applied Sciences

Image Compression Using Proposed Enhanced Run Length Encoding Algorithm

: Compression

RLE

Run length encoding

GIF

TIFF

PNG

JPEG

BMP

BMP header

BMP file

Compression ratio

Lossless

Lossy

True color.

A. H.

S. Sh.

R. J.

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In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm

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