International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 6, No. 11, 8 Oct. 2014
Cover page and Table of Contents: PDF (size: 514KB)
Performance Evaluation of Super Resolution Image Reconstruction using IWT and BPT with Different Colour Transforms
Full Text (PDF, 514KB), PP.62-68
Views: 0 Downloads: 0
Author(s)
P.Ashok Babu
1,*
K.V.S.V.R.Prasad
2
Index Terms
Super Resolution, Bi Cubic Interpolation, YCbCr, CIELAB, IWT, and BPT
Abstract
Super resolution (SR) images play an important role in Image processing applications. Spatial resolution is the key parameter in many applications of image processing. Super resolution images can be used to improve the spatial resolution. In this paper a new SR image reconstruction algorithm is proposed using Integer wavelet transform (IWT) and Binary plane technique (BPT). The proposed method is analyzed in different color space transforms such as CIELAB, YCbCr and RGB. In this paper we compared PSNR, ISNR, Blocking effect and Homogeneity with different colour images in RGB, YCbCr and CIELAB domains. Qualitative analysis shows that the proposed method in CIELAB color space transforms has better performance.
Cite This Paper
P.Ashok Babu, K.V.S.V.R.Prasad,"Performance Evaluation of Super Resolution Image Reconstruction using IWT and BPT with Different Colour Transforms", IJIGSP, vol.6, no.11, pp. 62-68, 2014. DOI: 10.5815/ijigsp.2014.11.08
Reference
[1]T. S. Huang and R. Y. Tsai, “Multi-frame image restoration and registration,” Adv. Comput. Vis. Image Process., vol. 1, pp. 317–339, 1984.
[2]M. E. Tipping and C. M. Bishop, “Bayesian image super-resolution,” Advances in Neural Information and Processing Systems 16, 2003.
[3]Dr. M.Ashok and Dr. T. Bhaskar Reddy, "Color image compression based on Luminance and Chrominance using Binary Wavelet Transform (BWT)and Binary Plane Technique (BPT)," International Journal of Computer Science and Information Technology & Security (IJCSITS) , vol. 1, no. 2, pp. 2249-9555 , 2012.
[4]N. Subhash Chandra et al., "Loss Less compression of Images using Binary Plane Difference and Huffman coding (BDH Technique) ," Journal of Theoretical and Applied Information Technology, vol. 3, no. 1, pp. 3-56, 2008.
[5]P.Ashok Babu,Dr.K.V.S.R.Prasad,” A lossy color image compression using IWT and BPT”,Graphics & Vision Vol:12,Iss:15,2012.
[6]R.C.Ganzalez “Digital Image Processing”, Pearson Education India.
[7]Ming-Ni Wu; Chia-Chen Lin; Chin-Chen Chang; , "Brain Tumor Detection Using Color-Based K-Means Clustering Segmentation," Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. vol.2, no., pp.245-250, 26-28 Nov. 2007
[8]S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, “Fast and robust multiframe super-resolution,” IEEE Transactions on Image Processing, vol. 13, pp. 1327–1344, 2004.
[9]N. Idrissi, J. Martinez, and D. Aboutajdine, “Selecting a discriminant subset of co-occurrence matrix features for texture-based image retrieval,” in Proc. ISVC05, 2005, pp. 696–703.
[10]Zhou Wang; Sheikh, H.R.; Bovik, A.C.; , "No-reference perceptual quality assessment of JPEG compressed images," International Conference on Image Processing Proceedings. 2002 vol.1, no., pp. I-477- I-480 vol.1,2002.
[11]Jianchoa Yang,Thomas Huang, “ Image super resolution: Historical overview and future challenges”. www.ifp.illinois.edu/~jyang29/papers/chap1.pdf - United States.