Abstract
Although lossless techniques should be preferred over lossy techniques it is not always the case. This is because lossy techniques tend to decrease the overall computational time. The method described below proposes a near lossless technique that works on the spatial domain and utilizes a few properties of pixel values to reduce significantly the bit representation size of the pixel values. This algorithm utilizes a new difference concept by dividing the pixel values into groups and using a fixed value for each block to be used as a difference factor. This algorithm also approaches compression by merging the red, green, and blue components into a single component with one third the size. The algorithm provides a level of compression that remains stable irrespective of the size or dimensions of the image while leaving an acceptable range of (30–50) PSNR that is also stable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Salomon, D.: Data compression the complete reference, 3rd edn. Springer Press, Heidelberg
Saffor, A., Ng, K.-H., Ramli, A.R.: A comparative study of image compression between Jpeg and wavelet. Malaysian J. Comput. Sci. 14(1), 39–45 (2001)
Pennebaker, W., Mitchell, J.: JPEG-still image data compression standards. Van Nostrand Reinhold (1993)
Padmaja, G.M., Nirupama, P.: Analysis of various image compression techniques. ARPN J. Sci. Technol. 2(4) (2012)
Acharya, T., Tsai, P.-S.: JPEG2000 Standard for Image Compression
Banerjee, A., Halder, A.: An efficient dynamic image compression algorithm based on block optimization, byte compression and run-length encoding along Y-axis. In: International Conference on Science and Information Technology (ICCSIT), (2010)
Ghosh, A., Chakraborty, D.: A lossy image compression by shrinking of repeating intensities in alternate dimensions and reducing bits for storage. In: ERCICA-2014, Bangalore, India, pp. 415–420
Halder, A, Dey, S., Mukherjee, S., Banerjee, A.: An efficient image compression algorithm based on block optimization and byte compression. In: ICISA-2010, Chennai, Tamilnadu, India (2010)
Das, N., Chakraborty, D.: An efficient compression for almost dual colored image using K-means clustering and block compression. In: ERCICA-2014, Bangalore, India, pp. 410–414
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Debashis Chakraborty, Shouvik Saha, Tanay Mukherjee (2016). Near Lossless Image Compression Using Block Division Byte Compression and Block Optimization. In: Shetty, N., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications . Springer, Singapore. https://doi.org/10.1007/978-981-10-0287-8_9
Download citation
DOI: https://doi.org/10.1007/978-981-10-0287-8_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0286-1
Online ISBN: 978-981-10-0287-8
eBook Packages: EngineeringEngineering (R0)