Performance Analysis of Chrominance Red and Chrominance Blue in JPEG
While compressing text files is useful, compressing
still image files is almost a necessity. A typical image takes up much
more storage than a typical text message and without compression
images would be extremely clumsy to store and distribute. The
amount of information required to store pictures on modern
computers is quite large in relation to the amount of bandwidth
commonly available to transmit them over the Internet and
applications. Image compression addresses the problem of reducing
the amount of data required to represent a digital image. Performance
of any image compression method can be evaluated by measuring the
root-mean-square-error & peak signal to noise ratio. The method of
image compression that will be analyzed in this paper is based on the
lossy JPEG image compression technique, the most popular
compression technique for color images. JPEG compression is able to
greatly reduce file size with minimal image degradation by throwing
away the least “important" information. In JPEG, both color
components are downsampled simultaneously, but in this paper we
will compare the results when the compression is done by
downsampling the single chroma part. In this paper we will
demonstrate more compression ratio is achieved when the
chrominance blue is downsampled as compared to downsampling the
chrominance red in JPEG compression. But the peak signal to noise
ratio is more when the chrominance red is downsampled as compared
to downsampling the chrominance blue in JPEG compression. In
particular we will use the hats.jpg as a demonstration of JPEG
compression using low pass filter and demonstrate that the image is
compressed with barely any visual differences with both methods.
[1] Kay, D. C. and Levine, J. R. 1995, Graphics File Formats, Windcrest,
McGraw-Hill.
[2] David Austin, "Image Compression: Seeing What's Not There"
[3] The International Telegraph and Telephone Consultative Committee
(CCITT). "Information Technology - Digital Compression and Coding
of Continuous-Tone Still Images -Requirements and Guidelines". Rec.
T.81, 1992.
[4] G. K. Wallace, "The JPEG Still Picture Compression Standard", IEEE
Trans. Consumer Electronics, Vol.38, No 1, Feb. 1992
[5] Douglas A. Kerr, P.E. "JPEG Compression of Still Images", Issue
1,August 16, 2003
[6] Home site of the JPEG and JBIG committees" http://www.jpeg.org/
(21/04/01).
[7] W. Pennebaker and J. Mitchell, JPEG, Still Image Data Compression
Standard, Van Nostrand Reinhold, 1993.
[8] Ramesh Neelamani, Ricardo de Queiroz, Zhigang Fan, and Richard
Baraniuk , "jpeg compression history estimation for color images"
[9] V. Bhaskaran, K. Konstantinides. Image and Video Compression
Standards Algorithms and Architectures - Second Edition, Kluwer
Academic Publishers, USA, 1999.
[10] J. Miano. Compressed Image File Formats - JPEG, PNG,GIF, XBM,
BMP, Addison Wesley Longman Inc, USA, 1999
[11] Charles Poynton, "A Technical Introduction to Digital Video, Wiley,
New York, 1996."
[12] N. Ahmed, T. Natarajan, and K. R. Rao, "Discrete cosine
transform,"IEEE Transactions on Computers, vol. C-32, pp. 90-93, Jan.
1974.
[13] Chen, W. H., and W. K. Pratt. 1984. Scene adaptive coder. IEEE
Transactions on Communications COM-32: 225-232.
[1] Kay, D. C. and Levine, J. R. 1995, Graphics File Formats, Windcrest,
McGraw-Hill.
[2] David Austin, "Image Compression: Seeing What's Not There"
[3] The International Telegraph and Telephone Consultative Committee
(CCITT). "Information Technology - Digital Compression and Coding
of Continuous-Tone Still Images -Requirements and Guidelines". Rec.
T.81, 1992.
[4] G. K. Wallace, "The JPEG Still Picture Compression Standard", IEEE
Trans. Consumer Electronics, Vol.38, No 1, Feb. 1992
[5] Douglas A. Kerr, P.E. "JPEG Compression of Still Images", Issue
1,August 16, 2003
[6] Home site of the JPEG and JBIG committees" http://www.jpeg.org/
(21/04/01).
[7] W. Pennebaker and J. Mitchell, JPEG, Still Image Data Compression
Standard, Van Nostrand Reinhold, 1993.
[8] Ramesh Neelamani, Ricardo de Queiroz, Zhigang Fan, and Richard
Baraniuk , "jpeg compression history estimation for color images"
[9] V. Bhaskaran, K. Konstantinides. Image and Video Compression
Standards Algorithms and Architectures - Second Edition, Kluwer
Academic Publishers, USA, 1999.
[10] J. Miano. Compressed Image File Formats - JPEG, PNG,GIF, XBM,
BMP, Addison Wesley Longman Inc, USA, 1999
[11] Charles Poynton, "A Technical Introduction to Digital Video, Wiley,
New York, 1996."
[12] N. Ahmed, T. Natarajan, and K. R. Rao, "Discrete cosine
transform,"IEEE Transactions on Computers, vol. C-32, pp. 90-93, Jan.
1974.
[13] Chen, W. H., and W. K. Pratt. 1984. Scene adaptive coder. IEEE
Transactions on Communications COM-32: 225-232.
@article{"International Journal of Information, Control and Computer Sciences:56523", author = "Mamta Garg", title = "Performance Analysis of Chrominance Red and Chrominance Blue in JPEG", abstract = "While compressing text files is useful, compressing
still image files is almost a necessity. A typical image takes up much
more storage than a typical text message and without compression
images would be extremely clumsy to store and distribute. The
amount of information required to store pictures on modern
computers is quite large in relation to the amount of bandwidth
commonly available to transmit them over the Internet and
applications. Image compression addresses the problem of reducing
the amount of data required to represent a digital image. Performance
of any image compression method can be evaluated by measuring the
root-mean-square-error & peak signal to noise ratio. The method of
image compression that will be analyzed in this paper is based on the
lossy JPEG image compression technique, the most popular
compression technique for color images. JPEG compression is able to
greatly reduce file size with minimal image degradation by throwing
away the least “important" information. In JPEG, both color
components are downsampled simultaneously, but in this paper we
will compare the results when the compression is done by
downsampling the single chroma part. In this paper we will
demonstrate more compression ratio is achieved when the
chrominance blue is downsampled as compared to downsampling the
chrominance red in JPEG compression. But the peak signal to noise
ratio is more when the chrominance red is downsampled as compared
to downsampling the chrominance blue in JPEG compression. In
particular we will use the hats.jpg as a demonstration of JPEG
compression using low pass filter and demonstrate that the image is
compressed with barely any visual differences with both methods.", keywords = "JPEG, Discrete Cosine Transform, Quantization,
Color Space Conversion, Image Compression, Peak Signal to Noise
Ratio & Compression Ratio.", volume = "2", number = "7", pages = "2423-4", }