Set Partitioning In Hierarchical Trees Coding Research Articles

A Visually Meaningful Image Encryption Scheme Based on Lossless Compression SPIHT Coding

With the popularity of social networks and the increase of cloud platform applications, service computing has also developed. Therefore, the protection of information even privacy uploaded to the cloud server has become critical. Recently, some researchers have proposed encryption schemes of visual meaningful image by using compressive sensing. However, these schemes generally cannot hide the large-size of plain image into the small-size of cover image and cannot recover the original plain image lossless. To solve above problems, this paper proposed a visually meaningful image encryption scheme based on lossless compression set partitioning in hierarchical trees (SPIHT) coding. The sender encrypts the plain image into the cipher image through the proposed encryption scheme, and then uploads the cipher image to the cloud server which is assumed as semi-honest trusted. Authorized receiver can completely decrypt the plain image after downloading the cipher image. In addition, even if the cipher image is attacked by attacker in the cloud server, the final decrypted image is still readable. Experimental results show that the proposed scheme is not only completely reversible and can hide the large-size of plain image into the small-size of cover image, but also superior to other schemes in visual quality and anti-attack performance.

Secure Image Watermarking in a Compressed SPIHT Domain Using Paillier Cryptosystem

A secure solution to the problem of copyright infringement and content authentication is to carry out image watermarking in secure signal processing (SSP) domain. Homomorphic encryption is considered one such solution for image watermarking in this domain. The Paillier encryption is found to be suitable for image processing applications in general and for watermarking in particular. In this article, a detailed investigation is carried out by using Paillier cryptosystem for twelve different color images in a compressed domain. The compression of the host images is carried out by SPIHT (Set Partitioning in Hierarchical Trees) coding. The visual quality of the images post embedding and image processing attacks is assessed by using two full reference metrics, Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The performance evaluation of the Paillier cryptosystem vis-à-vis watermark application development is carried out by computing three benchmark metrics: number of pixels change rate (NPCR), unified average changing intensity (UACI) and encryption speed.

A novel robust compression-encryption of images based on SPIHT coding and fractional-order discrete-time chaotic system

In this article, a novel robust compression-encryption of images based on Set partitioning in Hierarchical Trees (SPIHT) coding-decoding algorithm and synchronization of chaotic maps with non-integer order is proposed. The essential innovation in the proposed communication system is that the source image is compressed and encrypted by several secret keys. The developed transmission scheme is designed to take profit of two advantages. The first is the use of standard SPIHT coding which is an efficient and computationally very fast technique for image compression. The second is to introduce farther complexity to the cryptosystem through the use of fractional-order chaotic maps which has many advantages such as the generation of supplementary secret keys with respect to the discrete-time chaotic systems. From the obtained simulation results, we can see that the original image has been well encoded in the cipher text and retrieved with success through the chaotic signals. Further, to verify the high confidentiality of the presented cryptosystem, cryptanalysis is studied in detail through the various tests.

A selective compression-encryption of images based on SPIHT coding and Chirikov Standard Map

In this paper, we propose a partial compression-encryption of images using chaotic system and Discrete Wavelet Transform (DWT) combined with Set Partitioning in Hierarchical Trees (SPIHT). The proposed cryptosystem adopts three stages for confusion and diffusion which are well integrated into the compression chain. The chaotic system used in this approach is Chirikov Standard Map. Some cryptographic tests and metrics are applied to measure the degree of security and analyze the performance of the partial compression-encryption scheme. The evaluation and simulation analysis indicate that our proposal possesses excellent statistical and cryptographic properties; it is extremely sensitive to the small change in secret key, resists against common cryptanalytic attacks, has a high speed and provides high picture quality of the reconstructed image.

A joint image lossless compression and encryption method based on chaotic map

Nowadays poor security, low transmission and storage efficiency of images have become serious concerns. In order to improve the situation, this paper put forward a new image lossless compression joint encryption algorithm based on chaotic map with all original information intact. The lossless compression uses SPIHT(Set Partitioning in Hierarchical Trees) encoding method based on integer wavelet transform, and encrypt multiple rounds in the process of wavelet coefficients and SPIHT coding applying many kinds of chaotic maps. Experimental results show that the compressed file size is about 50 % of the original file size, which achieves relatively good lossless compression ratio. Besides, the encryption method passes many security tests, such as sensitivity test, entropy test, autocorrelation test, NIST SP800---22 test. There is a high application value in the medical field and the national security department whose image files require a relatively high quality.

Textual image compression at low bit rates based on region-of-interest coding

In this paper, we deal with those applications of textual image compression where high compression ratio and maintaining or improving the visual quality and readability of the compressed images are of main concern. In textual images, most of the information exists in the edge regions; therefore, the compression problem can be studied in the framework of region-of-interest (ROI) coding. In this paper, the Set Partitioning in Hierarchical Trees (SPIHT) coder is used in the framework of ROI coding along with some image enhancement techniques in order to remove the leakage effect which occurs in the wavelet-based low-bit-rate compression. We evaluated the compression performance of the proposed method with respect to some qualitative and quantitative measures. The qualitative measures include the averaged mean opinion scores (MOS) curve along with demonstrating some outputs in different conditions. The quantitative measures include two proposed modified PSNR measures and the conventional one. Comparing the results of the proposed method with those of three conventional approaches, DjVu, JPEG2000, and SPIHT coding, showed that the proposed compression method considerably outperformed the others especially from the qualitative aspect. The proposed method improved the MOS by 20 and 30 %, in average, for high- and low-contrast textual images, respectively. In terms of the modified and conventional PSNR measures, the proposed method outperformed DjVu and JPEG2000 up to 0.4 dB for high-contrast textual images at low bit rates. In addition, compressing the high contrast images using the proposed ROI technique, compared to without using this technique, improved the average textual PSNR measure up to 0.5 dB, at low bit rates.

PSNR Comparison of Lifting Wavelet Decomposed Modified SPIHT Coded Image with Normal SPIHT Coding

Today’s world is the era of communication i.e. sending some information from one point to another. And images are one of the commonly used multimedia, because of the application in almost every field of engineering i.e. biomedical, astronomical, geological etc. To make communication fast and efficient with respect to images, compression is needed in each and every field. Idea behind the work is to reduce the size of image at transmitter end and after sending it to the receiver, regenerate it again to its original form. But to attain a measurable amount of compression, there are always some losses (compromise on resolution) at receiver end. The measure of efficiency of compression coding depends upon the balance between resolution and compression ratio of images. So aim of every coding scheme is to make a good trade-off between resolution and compression ratio so that we can achieve a fast communication with a good regenerated image at the receiver end. In this work, compression is based on wavelet transform. Wavelet is an important tool to covert spatial domain representation into frequency domain which is not based on a fundamental frequency of sine or cosine waveform of infinite period of time but finite numbers of short waves of different frequencies which give the best result for high frequency components as well as for low frequency (long time period) components too. After transforming the image, lower and higher energy parts can be easily differentiated and quantization can be applied to truncate the unnecessary lower energy parts where higher energy is kept preserve. For coding of transformed image, a Set Partitioning in Hierarchical Tree (SPIHT) coding algorithm is used. After the transformation, SPIHT coding scheme basically code high energy components first and progressively transmits the coded bits to make an increasingly refined copy of the original image. A modified SPIHT coding is presented in the work for progressive transmission.

Medical Image Compression in WBCT Domain Using Fast FIC and SPIHT Coding

Fractal image coding encodes the input image with low bit rate and decodes the same with the reasonable quality of reconstruction. But, FIC has the demerit of longer time taken for encoding. In this paper, a fractal and SPIHT encoding of WBCT coefficients is proposed. Fast fractal encoding using particle swarm optimization (PSO) is applied to the low pass sub band of wavelet based contourlet transformed image and a modified set partitioning in hierarchical trees (SPIHT) coding is applied on the remaining coefficients. PSO technique and reduced domain pool size will speed up the fractal encoder, whereas the WBCT coefficients preserve the image quality in case of smooth contoured images. Furthermore, image details and wavelet progressive transmission characteristics are maintained. Experimental results prove that the proposed algorithm provides better quality of reconstruction with reduced bit rate.

Medical Image Compression Using Wavelets

With the development of CT, MRI, PET, EBCT, SMRI etc, the scanning rate and distinguishing rate of imaging equipment is enhanced greatly. Using wavelet technology, medical image can be processed in deep degree by denoising, enhancement, edge extraction etc, which can make good use of the image information and improve diagnosing. Compressions based on wavelet transform are the state-of-the-art compression technique used in medical image compression. For medical images it is critical to produce high compression performance while minimizing the amount of image data so the data can be stored economically. Modern radiology techniques provide crucial medical information for radiologists to diagnose diseases and determine appropriate treatments. Such information must be acquired through medical imaging (MI) processes. Since more and more medical images are in digital format, more economical and effective data compression technologies are required to minimize mass volume of digital image data produced in the hospitals. The wavelet-based compression scheme contains transformation, quantization, and lossless entropy coding. For the transformation stage, discrete wavelet transform and lifting schemes are introduced. In this paper an attempt has been made to analyse different wavelet techniques for image compression. Hand designed wavelets considered in this work are Haar wavelet, Daubechie wavelet, Biorthognal wavelet, Demeyer wavelet, Coiflet wavelet and Symlet wavelet. These wavelet transforms are used to compress the test images competitively by using Set Partitioning In Hierarchical Trees (SPIHT) algorithm. SPIHT is a new advanced algorithm based on wavelet transform which is gaining attention due to many potential commercial applications in the area of image compression. The SPIHT coder is also a highly refined version of the EZW algorithm.

A Hybrid Scheme Using Improved SPIHT and Huffman Coding for Lossless Image Compression

In order to improve the coding performance of image lossless compression, a hybrid lossless compression scheme based on modified Set Partitioning in Hierarchical Trees (SPIHT) and Huffman coding is proposed. The lower magnitude bit-planes, whose corresponding magnitude thresholds are less than 8, and the sign bit-plane are scanned node by node in the fixed order, and the bit sequence obtained by scanning the bit-planes is further processed by Huffman coder to remove the statistical redundancy. The other bit-planes, namely the higher magnitude bit-planes, are sorted by the modified SPIHT partitioning structure, which could improves the coding efficiency of sorting pass by means of grouping more nodes together. Experimental results show the proposed algorithm has reduced its bit-rate by 0.13bit/pixel-0.35bit/pixel for gray images and by 0.72bit/pixel-1.25bit/pixel for color images as compared with those of the original SPIHT algorithm. Furthermore, the modified scheme retains the progressive transmission property of SPIHT coder. It is concluded that the proposed method efficiently reduces the redundancy existing in the original SPIHT coder and is fit for lossless image compression.

Stereo Video Coding based on Depth Map and SPIHT

In this paper, we propose a scalable stereo video coding algorithm based on Depth estimation and Set Partitioning in Hierarchical Tree (SPIHT) codec. The new approach which combines depth estimation algorithm based on markov random field (MRF) and the wavelet transform technique makes it possible to realize scalable wavelet stereo video coding. Compared to traditional stereo video coding, we use depth estimation to get the depth map and detect the depth of different objects, the wavelet transform coefficients of near object in SPIHT codec will be classified in the significant sets and others insignificant. After SPIHT coding, the wavelet transform coefficients are divided into multiple independent sub-streams for transferring. The nearest of object is often the most frequent visitors of regional concern, so more details are reserved. Finally, we make some assessments to this algorithm in reduction ratio and visual effect. Simulation results on different video sequences show that the proposed method realizes low encoding complexity at the encoder and achieve efficient performance of stereo video compression.

电动汽车充电站监控系统录波数据压缩方法

为解决电动汽车充电站监控系统录波难度大、数据传输效率低的问题，本文引入一种2维离散小波变换、多级树集合分裂(set partitioning in hierarchical tree, SPIHT)编码、算术编码相结合的数据压缩新方法。该方法采用提升格式的2维离散小波变换对监测数据进行压缩，然后对小波系数进行SPIHT编码，最后采用算术编码实现压缩性能的控制，并进一步提高压缩比。对充电站中常见的电能质量谐波信号进行了压缩实验，结果表明该方法具有良好的压缩性能，验证了算法的有效性，在电动汽车充电站监控系统中具有较大的应用价值。 For solving the problem of recording waves difficulty and low transmission efficiency in monitoring system of electric vehicles charging station, a new method for data compression, which integrates two-dimension discrete wavelet transform (DWT) in lifting format and set partitioning in hierarchical tree (SPIHT) coding with drithmetic cod-ing, is introduced. The proposed method compressed monitoring data by means of two-dimension DWT in lifting for-mat, then the SPIHT coding is applied to wavelet coefficients, in the end, the drithmetic coding is used to control the compression performance and increase the compression ratio. The compression experiments of frequent power quality harmonic signals are performed, the results show that the proposed method has better compression performance, which verifies the effectiveness of the algorithm. This scheme has greater application value in monitoring system of electric vehicles charging station.

A hybrid image compression scheme using HVS characteristics: combining SPIHT- and SOFM-based vector quantisation

Nowadays, developing hybrid schemes for effective image compression has gained enormous popularity among researchers. A hybrid scheme combining Kohonen’s Self Organising Feature Map (SOFM) based Vector Quantisation (VQ) coding and Set Partitioning In Hierarchical Trees (SPIHT) coding for effective compression of images is proposed. This paper embeds Human Visual System (HVS) into SPIHT algorithm to proffer different perceptual weights to different image blocks. The SPIHT coder results with a bit stream, which is then fed to the SOFM, based VQ coding for compression. The experimental results demonstrate the improvement in CR and subjective visual quality of the images on reconstruction.

Enhancing the Color Set Partitioning in Hierarchical Tree (SPIHT) Algorithm Using Correlation Theory

Problem statement: Efficient color image compression algorithm is essential for mass storage and the transmission of the image. The compression efficiency of the Set Partitioning in Hierarchical Tree (SPIHT) coding algorithm for color images is improved by using correlation theory. Approach: In this study the correlation between the color channels are used to propose the new algorithm. The correlation between the color channels are analyzed in various color spaces and the color space CIE-UVW in which the color channels are highly correlated is taken. The most correlated U channel is considered as base color and compressed by using the wavelet filter and the SPIHT algorithm. The linear approximation of the two of the color components (V and W) based on the primary color component U is used to code subordinate color components. The image is divided into N*N blocks in each color channels. The linear approximation coefficients are calculated for each block of the subordinate colors V and W as functions of the base color. Only these coefficients of each block are coded and send to the receiver along with the SPIHT coding of the base color. Results: By using this algorithm, a significant (4 dB mean value) Peak Signal to Noise Ratio (PSNR) improvement is obtained compared to the traditional coding scheme for the same compression rate and reduces the coding and decoding time. Also the proposed compression algorithm reduces the complexity in coding and decoding algorithms. Conclusion: This algorithm allows the reduction of complexity for both coding and decoding of color images. It is concluded that a significant PSNR gain and visual quality improvement is obtained. It is found that in color image coding, this algorithm is superior to the traditional de-correlation based methods and reduces the coding and decoding time.

Combined significance map coding for still image compression

Set partitioning in hierarchical trees (SPIHT) was known for its relatively simple implementation and flexible scalability when it is combined with discrete wavelet transform (DWT). The authors propose a method called combined significance map coding (CSMC) to improve the coding efficiency of SPIHT when used with block-based discrete cosine transform (DCT). CSMC groups some blocks and encodes the combined significance map of one to several blocks together. Lots of bits spent in significance map coding can be saved when the trees constructed with block DCT coefficients have similar locality. From our simulation results, CSMC improves significantly when in comparison with the original SPIHT coder using DWT and DCT. It also yields better performance than JPEG2000, and even outperforms the non-scalable H.264 intra-mode coder for some test images. No coding table is required, and fine rate/quality scalability property of SPIHT is still preserved.

Evolutionary clustering based vector quantization and SPIHT coding for image compression

Taking both the correlations among and within wavelet subbands of images into account, in this paper we proposed an evolutionary clustering based vector quantization (VQ) and set partitioning in hierarchical trees (SPIHT) coding method for image compression. One-step gradient descent genetic algorithm (OSGD-GA) is designed for optimizing the codebooks of the low-frequency wavelet coefficient by defining the importance degree of each coefficient and utilizing fuzzy membership to address the automatic clustering. This new VQ technology exploits the global searching capability of OSGD-GA and can automatically obtain contextual constraints on membership condition by weighted average method of the importance, so it can overcome the drawbacks of classical clustering algorithm. Then the scalar quantization followed by SPIHT coding algorithm is employed for the high-frequency wavelet coefficients. Some simulational experiments are taken to investigate the performance of the proposed method. The results show that our proposed method not only brings about some new ideas in combining the evolutionary clustering based VQ and SPIHT coding, but also yields an improvement of PSNR to the greatest 0.66 dB over SPIHT algorithm.

Highly scalable hybrid image coding scheme

This paper describes a highly scalable hybrid image coding scheme (HS-HIC). The proposed hybrid coding scheme combines simply modification of the data in the wavelet domain and the high performance of the set partitioning in hierarchical trees (SPIHT) coding. The modification of the subband image data is done based on the transformation of the high-frequency subband (details) in the wavelet domain. It is based on linear modification of 9-subband image data within three-layer in the wavelet domain. Except the image data in LL3, all other image data will be linearly modified based on the discrete Fourier transform (DFT) components. The modification process provides a new subband image data containing almost the same information as the original one but having a smaller frequency spectrum. The modified data is then located in the corresponding position and the simple SPIHT coder followed by adaptive arithmetic coder is applied on the resulting hierarchical representation to generate the symbol stream. Simulation results demonstrate that, with small addition in the computational complexity of the coding process, the PSNR performance of the proposed algorithm is much higher than that of the SPIHT test coder and some of famous image coding techniques.

Color image steganography scheme using set partitioning in hierarchical trees coding, digital Fourier transform and adaptive phase modulation

In this research of color image hidden scheme, we aim to conceal a secret image into the cover image of the same size without noticeable degradation. In our approach, discrete wavelet transform (DWT) and set partitioning in hierarchical trees (SPIHT) codec are used to obtain a low bit rate and high reconstructed quality image compression. In the embedding process, an adaptive phase modulation (APM) mechanism and discrete Fourier transform (DFT) were adopted for secret data embedding. Simultaneously, nearest phase modulations (NPM) was used to improve the imperceptibility and decrease degradation of cover image. Both the chaotic mechanism (CM) and frequency hopping (FH) structure were hired to enhance the security of the scheme. Comparing with other data-hiding techniques, our proposed method has three advantages. (A) The extracted secret image has high quality reconstruction by using SPIHT coder. (B) The stego-image possesses excellent imperceptibility without noticeable degradation because secret data was concealed in the phase by using APM and NPM. (C) Have very large embedding capacity, it allows the size of secret image to be the same as the cover image.

A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure

The set partitioning in hierarchical trees (SPIHT) algorithm is an efficient wavelet-based progressive image-compression technique, designed to minimize the mean-squared error (MSE) between the original and decoded imagery. However, the MSE-based distortion measure is not in general well correlated with image-recognition quality, especially at low bit rates. Specifically, low-amplitude wavelet coefficients that may be important for classification are given low priority by conventional SPIHT. In this paper, we use the kernel matching pursuits (KMP) method to autonomously estimate the importance of each wavelet subband for distinguishing between different textures, with textural segmentation first performed via a hidden Markov tree. Based on subband importance determined via KMP, we scale the wavelet coefficients prior to SPIHT coding, with the goal of minimizing a Lagrangian distortion based jointly on the MSE and classification error. For comparison we consider Bayes tree-structured vector quantization (B-TSVQ), also designed to obtain a tradeoff between MSE and classification error. The performances of the original SPIHT, the modified SPIHT, and B-TSVQ are compared.

Adaptive zero-tree structure for curved wavelet image coding

We investigate the issue of efficient data organization and representation of the curved wavelet coefficients [curved wavelet transform (WT)]. We present an adaptive zero-tree structure that exploits the cross-subband similarity of the curved wavelet transform. In the embedded zero-tree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT), the parent-child relationship is defined in such a way that a parent has four children, restricted to a square of 2×2 pixels, the parent-child relationship in the adaptive zero-tree structure varies according to the curves along which the curved WT is performed. Five child patterns were determined based on different combinations of curve orientation. A new image coder was then developed based on this adaptive zero-tree structure and the set-partitioning technique. Experimental results using synthetic and natural images showed the effectiveness of the proposed adaptive zero-tree structure for encoding of the curved wavelet coefficients. The coding gain of the proposed coder can be up to 1.2 dB in terms of peak SNR (PSNR) compared to the SPIHT coder. Subjective evaluation shows that the proposed coder preserves lines and edges better than the SPIHT coder.