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ISSN: 0974-7230
Journal of Computer Science & Systems Biology
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Compression of Image with Different File Formats

Abdul Jabbar*

Bahauddin Zakariya University, Multan, Pakistan

*Corresponding Author:
Abdul Jabbar
Bahauddin Zakariya University
Multan, Pakistan
Tel: +92619210097
E-mail: [email protected]

Received Date: December 26, 2016; Accepted Date: January 25, 2017; Published Date: January 27, 2017

Citation: Jabbar A (2017) Compression of Image with Different File Formats. J Comput Sci Syst Biol 10:012-013. doi: 10.4172/jcsb.1000240

Copyright: © 2017 Jabbar A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Reducing the size of original data (Image, Audio, or Video) is called Data compression. Data compression is basically a technique in which data is represented with the help of fewer bits. These fewer bits (fewer pixels) will represent the original data as it is represented with the help of larger bits (larger pixels). With the help of lower bits (fewer pixels), the size of the data automatically decrease, it takes less storage space, faster writing and reading, it takes less time during the uploading and downloading. Whether you’re dealing with images, music, or video files, it’s important to understand the difference between different types of formats and when to use them. Using the wrong format could ruin a file’s quality or make its file size unnecessarily large. In this paper, I present a comparison among different image formats in the form of table, so that the user will decide which image format is better to use before using it.

Keywords

File formats; Lossy data compression; Lossless data compression; Data compression

Introduction

Images are very important documents nowadays; to work with them in some applications they need to be compressed, the main idea in image compression is to reduce the data stored in the original image to a smaller amount, the reduced file is called the compressed file and reconstitute file, is called the decompressed file. During decompressing, the original file may be fully recovered from the original file without any loss of actual information but some time, the original file may not be fully recovered from the original file due to loss of some information [1]. This process is divided into following two categories based on fully recovered data and not fully recovered data- Lossless Compression and Lossy Compression (Figure 1).

computer-science-systems-biology-Compression-data

Figure 1: Compression of data.

Lossless compression

Lossless compression is basically a technique where loss of information is zero means original image or file can be recovered without the loss of any kind of information, the original file is recovered when it is uncompressed (Figure 2) [2].

computer-science-systems-biology-decompressed-image

Figure 2: Sizes of original and decompressed image are same.

Lossy compression

Lossy compression is basically a technique where loss of information is not zero means original image or file cannot be recovered without the loss of any kind of information. The original file cannot be recovered when it is uncompressed (Figure 3) [2].

computer-science-systems-biology-decompressed-image

Figure 3: Sizes of original and decompressed image are not same.

From Figures 2 and 3, it is clear that the original file cannot be reconstituted when we apply lossy compression methods and original file can be reconstitute when we apply lossless compression methods on file. But is does not mean that lossy compression methods cannot be used in compression because there are some advantages along with its disadvantages. Some image formats have advantages to use lossy compression and some have advantages to use lossless data compression.

Proposed Work

In our work, we are going to going to present a table of different image formats to give a clear comparison between lossy and lossless compression methods (Table 1).

SNo Format Name Compressed Method
1 JPEG Joint Photographic Experts Group Lossy
2 GIF Graphic Interchange Format Lossless
3 TIFF Tagged Image File Format Lossless
4 PNG Portable Network Graphics Lossless
5 BITMP Bitmapped Graphics Format Lossless
6 RAW Raw Image Format Lossless
7 PSD Photoshop Document Lossless
8 DGN Digital Negative Lossless
10 SVG Scalable Vector Graphics Lossless
11 SWF Shockwave Flash Lossless
12 XCF Gimp Project File Lossless/Lossy
13 PPM Portable Pixmap Lossy
14 EXIF Exchangeable Image File Format Lossy
15 CGM Computer Graphics Metafile Lossy
16 PAM Portable Arbitrary Map Lossy
17 MPO Multi Picture Format Lossy
18 JPS Jpeg Stereo Lossy
19 WMF Window Metafiles Lossy/Lossless
20 WEBP Webp Lossy
21 ILBM Interleaved Bitmap Lossless
22 RLE Run Length Encoding Lossless
23 IFF Interchange File Formats Lossless
24 GPL General Public License Lossless
25 PGF Graphics Interchange Format Lossless

Table 1: Comparison between lossy and lossless compression methods

Conclusion

Clearly, our proposed table is not very technical but it can help to improve some existing compression methods. This paper demonstrates some useful image formats to give clear idea to user that which image format is better to use in which scenario. This table also give the idea about compression of image that how much an image is compressed (size is reduced in the form of pixels).

References

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