An efficient macroblock-based diverse and flexible prediction modes selection for hyperspectral images coding

  • Authors:

  • Fan Zhao;Guizhong Liu;Xing Wang

  • Affiliations:

  • School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China and Department of Information Science, Xi'an University of Technology, Xi'an 710048, China;School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China;School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China

  • Venue:
  • Image Communication
  • Year:
  • 2010

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Abstract

In this paper, an efficient macroblock-based diverse and flexible prediction modes selection algorithm is proposed for coding hyperspectral images, which is inspired by the prediction scheme of H264/AVC. Here, different modes are specified for the corresponding macroblocks (16x16 pixel regions of a band) of hyperspectral images other than the whole band image using only one reference band image for prediction. Only the 4x4 mode is employed for the intra-band prediction in view of the fact that correlation coefficients of pixels separated by not more than four pixels in the spatial domain are greater than 0.65 at most cases. The optimal reference band is determined by the fast reference band selection algorithm; thereafter, the best partition of the candidate macroblock in the optimal reference band is further selected for inter-band prediction of the current macroblock. Thus, the stronger correlation in the spectral direction or in the spatial domain is utilized for the prediction of the given macroblock. With a comparably low memory requirement, the prediction coding scheme is proposed to speed up the implemental process using the fast reference band selection algorithm, the integer DCT and the quantization, which just needs the multiplication and bit-shifts operations. Several AVIRIS images are used to evaluate the performance of the algorithm. The proposed scheme outperforms the state-of-the-art 3D-based compression algorithms at lower rates. Moreover, compared with the method by using all the prediction modes of H.264/AVC, about 80% encoding time can be saved by our method under the same experimental condition.