Inter-band Prediction Research Articles

Reversible data hiding in multispectral images for satellite communications

The Landsat multispectral images are taken by satellites and then transmitted to the monitor center on the ground. Due to that governments and companies sometimes transmit secret messages through the satellite channel, the transmitting process of multispectral images can be a good cover for the secret messages by applying reversible data hiding (RDH) technology. This work proposed a novel RDH method for multispectral images. Before data embedding, each band is creatively matched with a reference band to perform the proposed inter-band complexity computation and inter-band prediction. For the pixels of the to-be-embedded band, we inventively combine the proposed inter-band complexity and the inter-space complexity to classify them into four categories and then process them by the inter-space predictor, inter-band predictor, multi-predictor and second-time prediction, respectively. Moreover, a general complexity is used to control the embedding priority to achieve lower distortion. Compared with the generally used reversible data hiding methods, our proposed method can reach a larger embedding rate and lower distortion for multispectral images.

Lossless compression of hyperspectral images using hybrid context prediction

In this letter a new algorithm for lossless compression of hyperspectral images using hybrid context prediction is proposed. Lossless compression algorithms are typically divided into two stages, a decorrelation stage and a coding stage. The decorrelation stage supports both intraband and interband predictions. The intraband (spatial) prediction uses the median prediction model, since the median predictor is fast and efficient. The interband prediction uses hybrid context prediction. The hybrid context prediction is the combination of a linear prediction (LP) and a context prediction. Finally, the residual image of hybrid context prediction is coded by the arithmetic coding. We compare the proposed lossless compression algorithm with some of the existing algorithms for hyperspectral images such as 3D-CALIC, M-CALIC, LUT, LAIS-LUT, LUT-NN, DPCM (C-DPCM), JPEG-LS. The performance of the proposed lossless compression algorithm is evaluated. Simulation results show that our algorithm achieves high compression ratios with low complexity and computational cost.

Compressed Hyperspectral Image Sensing Reconstruction Based on Interband Prediction and Joint Optimization

基于高光谱图像压缩采样数据特性的分析，提出一种基于谱间预测和联合优化的压缩感知图像重构算法。首先在谱间通过线性预测去除高光谱图像观测向量的强谱间相关性，得到熵值更小的预测残差向量；然后在凸集交替投影(Projections Onto Convex Sets, POCS)的基础上提出基于最陡下降法的联合优化算法对预测残差向量进行重构，提高重构质量；同时采用像素点为指导的收敛准则提高算法的收敛速度。实验结果表明，在相同观测值数目下，该文算法的重构质量(PSNR)明显优于其它已有重构算法，并且具有较低的计算复杂度。

Lossless Hyperspectral Image Compression System-Based on HW/SW Codesign

The design and implementation of a lossless compression system for hyperspectral images on a processor-plus-field-programmable gate array (FPGA)-based embedded platform. Software execution time of compression algorithm was profiled first to conclude the decision of accelerating the most time consuming interband prediction module by hardware realization. Efficient algorithm to hardware mapping led to a high throughput accelerator design in FPGA capable of processing 16.5 M pixels/s. A set of optimization techniques were applied systematically to enhance the overall system performance. These include a hierarchical memory access scheme to resolve the bus bandwidth limitation, DMA assisted data transfers to shorten the hardware/software (HW/SW) communication, and various coding style and compiler options to optimize the software execution. The final result shows a 21 speed-up compared to a purely software implementation and the performance was actually bounded by the software section in realizing an entropy coder. A 27 speed-up can be achieved if a simplified coder is used.

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

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 (16×16 pixel regions of a band) of hyperspectral images other than the whole band image using only one reference band image for prediction. Only the 4×4 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.

Optimal Recursive Bidirection Prediction for Hyperspectral Image Compression

In this paper, we propose a new algorithm named Optimal Recursive Bidirection Prediction (ORBP) for HyperSpetral Image (HSI) compression. Recursive Bidirection Prediction (RBP) is a good algorithm for HSI inter-band prediction. It's simple, efficient. But the algorithm can't get optimal prediction result under the sense of SNR. In this paper, the linear model of HSI is established, and the best prediction is deduced under the sense of SNR. The proposed method can get lower entropy after prediction. Computer simulation results show that compared with the traditional algorithm RBP, the proposed method ORBP has a great improvement by about 9.2738dB in SNR in average.

Multiresolution Vector Quantization for Video Coding

In this work, we propose a coding technique that is based on the generalized block prediction of the multiresolution subband decomposition of motion compensated difference image frames. A segmentation mask is used to distinguish between the regions where motion compensation was effective and those regions where the motion model did not succeed. The difference image is decomposed into a multiresolution pyramid of subbands where the highest resolution subbands are divided into two regions, based on the information given by the segmentation mask. Only the coefficients of the regions corresponding to the motion model failure are considered in the highest resolution subbands. The remaining coefficients are coded using a multiresolution vector quantization scheme that exploits inter-band non-linear redundancy. In particular, blocks in one subimage are predicted from blocks of the adjacent lower resolution subimage with the same orientation. This set of blocks plays the role of a codebook built from coefficients inside the subband decomposition itself. Whenever the inter-band prediction does not give satisfactory results with respect to a target quality, the block coefficients are quantized using a lattice vector quantizer for a Laplacian source.

Haar wavelet transform with interband prediction and its application to image coding

AbstractAlthough the discrete cosine transform (DCT) and wavelet transform have been used as effective techniques for reducing the redundancy of image waveforms, they have the problems of high complexity and causing block distortion. In this paper, a Haar wavelet transform with interband prediction is proposed that permits high‐speed processing and which is suitable for coding as a subband decomposition technique since it generates little block distortion in the decoded images. the interband prediction method of this proposed transform method uses the derivative of the low‐band waveform to predict the high‐band waveform each time a band is split into two sub‐bands. This results in a transform process that gives a prediction residual signal with lower entropy. During the inverse transform, the prediction coefficients obtained from the forward transform are used to predict the high‐frequency waveforms and then, by adding the prediction residual, the original high frequency waveforms are reconstructed. Because the high‐frequency waveforms are generated that smoothly interpolate the up‐sampled, low‐frequency waveforms, any block effects from this prediction technique are difficult to see in the decoded image. A detailed analysis of the proposed interband prediction process is performed by interpreting the proposed transform as a subband decomposition process that is based on the use of a symmetric short‐kernel filter (SSKF) filter bank; then experiments are conducted that demonstrate its performance as a subband decomposition for coding of real image data and the possibility of progressive build‐up of the decoded images. Results show that this transform method is effective for coding image data.

Wavelet transform coding for MCP error images using quadtree decomposition and ECVQ

Abstract This paper proposes a new wavelet transform video coder which employs motion compensation, wavelet decomposition, and entropy-constrained vector quantization (ECVQ), in sequence. Each of layered subimages obtained from wavelet decomposition is segmented into basic blocks, and then the blocks are selectively encoded by ECVQ according to the energy of the samples. We introduce an efficient method to encode the map representing which blocks are encoded, based on inter-band prediction followed by a quadtree encoding. The proposed coder uses a simple forward analyzer in order to optimize the encoding parameters and introduces a preprocessing of signals which normalizes the input vectors of ECVQ in order to reduce the image-dependency of ECVQ codebooks. Simulation results show that our video coder provides good PSNR (peak-to-peak signal-to-noise ratio) performance and efficient rate control.

A modified short-kernel filter pair for perfect reconstruction of HDTV signals

A modified short-kernel filter pair is proposed for perfect reconstruction of HDTV signals. An interband prediction scheme based on the proposed filter pair is suggested to further reduce the average entropy of subband luminance signals. Simulations are conducted, and a modest reduction of the average entropy is obtained. >