Performance Research on Turbo TCM Schemes Using Different Set Partitioning Strategies for Fading Channels

Two different set partitioning strategies used in Turbo TCM, UP （Ungerboeck Partitioning） and BP （Block Partitioning） are compared over Rayleigh fading channels. The performance of Turbo TCM with the two set partitioning strategies and different frame length over Rayleigh fading channels is evaluated. The simulation results of 8PSK and 8ASK modulation and some significant conclusions are also given in this paper.

A New Approach Based on Set Partitioning in Hierarchical Tree Algorithm for Image Compression

In this paper, the authors propose a new approach to image compression based on the principle of Set Partitioning in Hierarchical Tree algorithm （SPIHT）. Our approach, the modified SPIHT （MSPIHT）, distributes entropy differently than SPIHT and also optimizes the coding. This approach can produce results that are a significant improvement on the Peak Signal-to-Noise Ratio （PSNR） and compression ratio obtained by SPIHT algorithm, without affecting the computing time. These results are also comparable with those obtained using the Embedded Zerotree Wavelet （EZW） and Joint Photographic Experts Group 2000 （JPG2） algorithms.

CONSTRAINED VITERBI ALGORITHM AND ITS APPLICATION TO ERROR RESILIENT TRANSMISSION OF SPIHT CODED IMAGES

To overcome some drawbacks of Viterbi algorithm （VA）, such as exponential growing complexity of decoding, and its poor performance under bad channel conditions, some available known information must be used as constrained condition and apriori knowledge for decoding. A new constrained VA is proposed by adding con- straint bits directly for conventional codec. Compared with the conventional VA, under the bad channel condi- tion, the proposed scheme can improve the peak signal to noise ratio （PSNR） of the decoding image 2--10 dB by changing the number of constrained bits. Experimental results show that it is an efficient error-controlling way for the transmission of set partitioning in hierarchical trees （SPIHT） coded image.

Formal Photograph Compression Algorithm Based on Object Segmentation

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.

Simultaneous Speckle Reduction and SAR Image Compression Using Multiwavelet Transform

Synthetic aperture radar （SAR） images are corrupted by multiplicative speckle noise which limits the performance of the classical coder/decoder algorithm in spatial domain. The relatively new transform of multiwavelets can possess desirable features simultaneously, such as orthogonality and symmetry, while scalar wavelets cannot. In this paper we propose a compression scheme combining with speckle noise reduction within the multiwavelet framework. Compared with classical set partitioning in hierarchical trees （SPIHT） algorithm, our method achieves favorable peak signal to noise ratio （PSNR） and superior speckle noise reduction performances.

New Edge-Directed Interpolation Based-Lifting DWT and MSPIHT Algorithm for Image Compression

The amount of image data generated in multimedia applications is ever increasing. The image compression plays vital role in multimedia applications. The ultimate aim of image compression is to reduce storage space without degrading image quality. Compression is required whenever the data handled is huge they may be required to sent or transmitted and also stored. The New Edge Directed Interpolation (NEDI)-based lifting Discrete Wavelet Transfrom (DWT) scheme with modified Set Partitioning In Hierarchical Trees (MSPIHT) algorithm is proposed in this paper. The NEDI algorithm gives good visual quality image particularly at edges. The main objective of this paper is to be preserving the edges while performing image compression which is a challenging task. The NEDI with lifting DWT has achieved 99.18% energy level in the low frequency ranges which has 1.07% higher than 5/3 Wavelet decomposition and 0.94% higher than traditional DWT. To implement this NEDI with Lifting DWT along with MSPIHT algorithm which gives higher Peak Signal to Noise Ratio (PSNR) value and minimum Mean Square Error (MSE) and hence better image quality. The experimental results proved that the proposed method gives better PSNR value (39.40 dB for rate 0.9 bpp without arithmetic coding) and minimum MSE value is 7.4.

A simple and efficient method for image transmission over inferior channel

The constrained Viterbi algorithm （C-VA） makes use of some prior reliable information to reduce complexity and improve performance of Viterbi algorithm （VA）. However it can only be used in the concatenate code scheme because the detection result of cyclic redundancy check code （CRC） is exploited to provide reliable information. In this paper, a different way is proposed to provide reliable information for C-VA, which is possible to be used in simple codec. Known bits were added to the set partitioning in hierarchical trees （SPIHT） coded image sequence periodically and directly. They were thought to be reliable information for C-VA in the decoder. Experimental results show that the proposed scheme can obtain much better error resilient ability compared with conventional VA under the extremely inferior channel condition if the best desired quality of reconstructed images can be sacrificed.

Rate-distortion weighted SPIHT algorithm for interferometer data processing

As one of the next generation imaging spectrometers, the interferential spectrometer （iS） possesses the advantages of high throughput, multi-channel and great resolution. The data of IS are produced in the spatial domain, but optical applications are in the Fourier domain. Traditional compression methods can only protect the visual quality of interferometer data in the spatial do- main but ignore the distortion in the Fourier domain. The relation between the distortion in the Fourier domain and the compression in the spatial domain is analyzed. By mathematical proof and val- idation with experiments, the relation between spatial and Fourier domains is discovered, and the significance in the Fourier domain is more important as optical path difference （OPD） increasing in the spatial domain. Based on this relation, a novel coding scheme is proposed, which can compress data in the spatial domain while reducing the distortion in the Fourier domain. In this scheme, the bit stream of the set partitioning in hierarchical trees （SPIHT） is truncated by adaptively lifting rate-distortion slopes according to the priorities of OPD based on rate-distortion optimization theory. Experimental results show that the proposed method can provide better protection of spectrum curves in the Fourier domain while maintaining a comparable visual quality in the spatial domain.

A COMPRESSION ALGORITHM FOR ECG BASED ON INTEGER LIFTING SCHEME WAVELET TRANSFORM

In view of the shortcomes of conventional ElectroCardioGram (ECG) compression algo- rithms,such as high complexity of operation and distortion of reconstructed signal,a new ECG compression encoding algorithm based on Set Partitioning In Hierarchical Trees (SPIHT) is brought out after studying the integer lifting scheme wavelet transform in detail.The proposed algorithm modifies zero-tree structure of SPIHT,establishes single dimensional wavelet coefficient tree of ECG signals and enhances the efficiency of SPIHT-encoding by distributing bits rationally,improving zero-tree set and ameliorating classifying method.For this improved algorithm,floating-point com- putation and storage are left out of consideration and it is easy to be implemented by hardware and software.Experimental results prove that the new algorithm has admirable features of low complexity, high speed and good performance in signal reconstruction.High compression ratio is obtained with high signal fidelity as well.

A wavelet packet based block-partitioning image coding algorithm with rate-distortion optimization

As an elegant generalization of wavelet transform, wavelet packet （WP） provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quanUzation scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.

An Efficient Multidimensional Fusion Algorithm for IoT Data Based on Partitioning

The Internet of Things （IoT） implies a worldwide network of interconnected objects uniquely addressable, via standard communication protocols. The prevalence of IoT is bound to generate large amounts of multisource, heterogeneous, dynamic, and sparse data. However, IoT offers inconsequential practical benefits without the ability to integrate, fuse, and glean useful information from such massive amounts of data. Accordingly, preparing us for the imminent invasion of things, a tool called data fusion can be used to manipulate and manage such data in order to improve process efficiency and provide advanced intelligence. In order to determine an acceptable quality of intelligence, diverse and voluminous data have to be combined and fused. Therefore, it is imperative to improve the computational efficiency for fusing and mining multidimensional data. In this paper, we propose an efficient multidimensional fusion algorithm for IoT data based on partitioning. The basic concept involves the partitioning of dimensions （attributes）, i.e., a big data set with higher dimensions can be transformed into certain number of relatively smaller data subsets that can be easily processed. Then, based on the partitioning of dimensions, the discernible matrixes of all data subsets in rough set theory are computed to obtain their core attribute sets. Furthermore, a global core attribute set can be determined. Finally, the attribute reduction and rule extraction methods are used to obtain the fusion results. By means of proving a few theorems and simulation, the correctness and effectiveness of this algorithm is illustrated.

On Pattern Avoiding Flattened Set Partitions

Let Π = B1/B2/… /Bk be any set partition of[n]= {1,2,...,n} satisfying that entries are increasing in each block and blocks are arranged in increasing order of their first entries.Then Callan defined the flattened Π to be the permutation of[n]obtained by erasing the divers between its blocks,and Callan also enumerated the number of set partitions of[n]whose flattening avoids a single3-letter pattern.Mansour posed the question of counting set partitions of[n]whose flattening avoids a pattern of length 4.In this paper,we present the number of set partitions of[n]whose flattening avoids one of the patterns：1234,1243,1324,1342,1423,1432,3142 and 4132.