Proc. SPIE. 9273, Optoelectronic Imaging and Multimedia Technology III
KEYWORDS: Signal to noise ratio, Wavelet transforms, Data compression, Image compression, Data storage, Wavelets, Chromium, Computer programming, Discrete wavelet transforms, New and emerging technologies
New technologies such as multi-dimension, multi-components and high precision methods adopted in seismic
exploration make seismic exploration data increase explosively. Large volume seismic data results in serious problems in
transmission, storage and processing of the data. In this paper a seismic data compression method based on wavelet
transform is proposed. The original data is decomposed into 12 detail sub-bands and 1 low-resolution sub-band with 2-
dimensional discrete wavelet transform. The wavelet coefficients of seismic data are encoded with embedded zero-tree
wavelet coding algorithm. Experimental results show that the proposed method is capable of efficient compression.
In this paper, an ultrasonic televiewer image encoding method based on block prediction is proposed. The original image
is divided into blocks of 8-by-8 pixels. The current block to be encoded is predicted from previously encoded and
decoded blocks. The prediction mode that minimizes the differences between the original and predicted is chosen from 9
modes. The prediction difference block is transformed with Discrete Cosine Transform (DCT), and the DCT coefficients
are quantized and encoded with lossless algorithm. The prediction modes selected are also encoded. Experimental results
show that the performance of the proposed method is much better than JPEG.
Iterated Function System (IFS) has been used to generate fractal graphics and fractal Chinese characters. A fractal
Chinese character magnification method is proposed in this paper to zoom in on arbitrarily selected areas within a fractal
Chinese character. For any selected area, a geometric transform is done to make the selected area occupy the full display
area. The mapping coefficients of the IFS for the Chinese character are modified such that the fractal pattern of the
Chinese character in the selected area can be just shown in the full display area. The experimental results demonstrate
that details are shown clearly with the magnification factor being more than 10000.
Fractal graphics, generated with iterated function systems (IFS), have been applied in broad areas. Since the collage
regions of different IFS may be different, it is difficult to respectively show the attractors of iterated function systems in
a same region on a computer screen using one program without modifying the display parameters. An algorithm is
proposed in this paper to solve this problem. A set of transforms are repeatedly applied to modify the coefficients of the
IFS so that the collage region of the resulted IFS changes toward the unit square. Experimental results demonstrate that
the collage region of any IFS can be normalized to the unit square with the proposed method.
The theory of iterated function systems (IFS) has been used in generating fractal graphics. In this paper, a method is
proposed to generate fractal Chinese characters with IFS. A Chinese character consists of strokes. In most cases, one
stroke is modeled with one affirn mapping. The finite set of the contractive affirn mappings that model all the strokes
construct the IFS for that Chinese character. Formulas to determine the coefficients of the IFS are deduced in this paper,
and the random iteration algorithm is used to show the fractal Chinese character. The experimental results show that the
generated fractal Chinese characters are self-similar and beautiful.
Global motion estimation (GME) has attracted great attentions because of its broad applications in video coding, image
stabilization, object segmentation and detection. In this paper, Fourier transform formula of the image after global
motion with a 6-parameter affine model is deduced, and its special cases for the 4-parameter and 5-parameter affine
model are discussed. A method for the global motion estimation using the 5-parameter affine model is proposed based on
the Fourier transform properties of the tow images before and after global motion. Simulation results show that the 5
affine parameters can be satisfactorily estimated.
In this paper, a method of IFS-based image geometry transform is proposed. Suppose the original image can be
approximated with the attractor (denoted by A) of an Iterated Function System (IFS) consisting of N contractive
mappings of wn (n=1, 2, ..., N), whose coefficients have been determined by fractal encoding. G(A) is used to denote the
geometry transform on the attractor A. The result is equivalent to make a corresponding geometry transform on the
original image. It is demonstrated in the paper that G(A) is the attractor of a new iterated function system (denoted by
IFS') derived from the mappings of wn (n = 1, 2, ...N). In another word, we can modify the coefficients of wn (n=1, ...,
N) to construct the IFS', and the result by decoding IFS' is A' = G(A), which is the approximation of the expected
geometry transform of the original image. In order to translate, rotate and dilate images in the domain of IFS coefficients,
formulas to construct the IFS' from wn are deduced in this paper. The experimental results have validated the proposed
Video systems have been widely used in many fields such as conferences, public security, military affairs and medical
treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video
processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the
purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the
system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet
controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system.
In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have
been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments
through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP
protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application
program scheme is proposed.
With the rapid development of the electronic technology, multimedia technology and network technology, video
monitoring system is going to the embedded, digital direction. In this paper, a solution of embedded video monitoring
system based on OMAP5912 is proposed. This solution makes full use of the advantages of dual-core of OMAP, which
include ARM core and DSP core. Non-realtime task such as user interface and control unit is assigned to ARM, and realtime
task such as video encoding is assigned to DSP. The capture and control task of the ARM side and the video
encoding task of the DSP side are described in detail. The experiments demonstrate that the video encoding speed has
been greatly improved by the proposed system comparing with the single ARM chip system. The frame rate of the
monitoring system is increased in a large scale, and more suitable for the application in practice.
Motion estimation and compensation play important roles in video coding. The most commonly used motion estimation
technique is block matching. In recent years, the global motion compensation (GMC) is paid great attentions because it is
an important tool for a variety of video processing applications including for instance registration, segmentation and
video coding. The phase correlation is a typical global motion estimation (GME) method in frequency domain. In this
paper, a new 4-parameter GME method is proposed based on the Fourier transform properties of the tow images before
and after global motion. At first, the scale and rotation parameters of the affine transform are estimated according to the
formulas derived in this paper. Then the effect of scale and rotation of the affine transform are corrected with the
estimated parameters. After that, the well-known phase correlation technique is used to determine the two shift
parameters. An algorithm according to this principle is proposed in this paper, and simulation results show that the 4
affine parameters can be exactly estimated with our new method.
In this paper, an IP-based video lab-monitor system is proposed in order to efficiently supervise and manage the Electrical Engineering Example Lab Center of Hubei Province. The proposed system is composed of one Control & Display Unit (CDU) and a number of Lab View Units (LVU). The CDU is placed in the lab-supervisor’s office, while each LVU with a video camera is placed in one of the labs to be watched. The CDU and all LVUs are connected with an IP network. An LVU is mainly composed of 4 parts: Video Capture, Video Encoder based on H.263, Media Deliverer and Communication Controller. Accordingly, the CDU is composed of the following parts: a Center Controller, a Media Receiver, a Multi-Video Decoder and a Multi-Video Displayer. The supervisor can simultaneously watch the dynamic scene of 16 (4x4) labs on the CDU, with a resolution of 176 x 144 for each lab. He may choose to watch 4 (2x2) labs or only one lab at a time with higher resolution.
Architecture of an IP-based narrow-band videophone system is proposed in this paper for convenient videophone calls between any two computers even if being placed in two different LANs within network agents. The bandwidth need of each call is less than 256 kbps. The system consists of two kinds of entities: Videophone Terminals (VPT) and a Video Call Server (VCS). A VPT is actually a microcomputer program, composed of 4 primary parts, an audio codec, a video codec, a media deliverer/receiver and a call controller. The basic functions of the VCS include videophone number generation and management, access admission and address resolution. The VCS with a public IP address plays an important role in the system especially when a video call has to penetrate through network agents. Each VPT in the system gets its own external transport address from the VCS through registration process. A calling VPT would receive the external transport address of the called VPT from the VCS through address resolution. The proposed system works and is helpful to accelerate the realization of people's videophone dream over IP networks.
The scalable image coding is an important objective of the future image coding technologies. In this paper, we present a kind of scalable image coding scheme based on wavelet transform. This method uses the famous EZW (Embedded Zero tree Wavelet) algorithm; we give a high-quality encoding to the ROI (region of interest) of the original image and a rough encoding to the rest. This method is applied well in limited memory space condition, and we encode the region of background according to the memory capacity. In this way, we can store the encoded image in limited memory space easily without losing its main information. Simulation results show it is effective.
Motion estimation plays an extremely important role in video coding. The objective of the motion estimation is to remove the temporal redundancy between video frames so that the video sequences can be coded efficiently. In this paper, an improved fast motion estimation algorithm, based on the successive elimination algorithm (SEA) of Li and Salari, is studied. This fast motion estimation algorithm results in the same displacement vectors as the exhaustive search algorithm (ESA) with a reduced computational load. An improved fast motion estimation algorithm, introducing further computational load reduction with negligible distortion, is proposed, and a transform coder based on the improved algorithm is developed. Implementation issues are discussed and compared. Experimental results show that the number of searching operations can be reduced dramatically with the help of the fast motion estimation algorithm.
On solving the access network bottleneck problem (usually known as the last mile problem), Ethernet passive optical network (EPON) is paid a great many attentions. Many works have been done on TDMA-based EPON system. Architecture of a WDM-based EPON system is proposed in this paper. The proposed system consists of one OLT, 1:32 Splitter/combiner, 32 ONUs and a Network Management System (NMS). The OLT includes a Service Node Interface (SNI), an Ethernet switch, an ODN Interface and a Network Management agent, while the ONU includes a User Side Interface (USI), an Ethernet Frame Forwarding, an ODN Interface and a Network Management agent. The downstream data are broadcast from the OLT to all ONUs with 1.25Gbps of line speed. Each ONU send the upstream data encapsulated in Ethernet frames up to OLT with specific wavelength and the 125Mbps of line speed. The upstream signals from all ONUs are aggregated to one fiber by the 1:32 combiner. When the aggregated stream arrives at the OLT, it is de-multiplexed and converted into 32 pairs of signals for more processing. As a result, all ONUs can send data to the OLT simultaneously. Experimental results show that our WDM-based EPON system works well.
A new method is proposed, in this paper, to magnify a portion of an image based on the fact that fractal attractor has details at every scale. The formulae for magnifying image portions with fractal method are deduced. The fractal codes, the coefficients of a set of contraction mappings, are determined by encoding the portion to be magnified. The fractal codes are then modified according to the formulae deduced in this paper, and the magnified image is obtained by decoding the modified fractal codes. A portion of Lenna image is enlarged by a factor of 8 at both horizontal and vertical directions with 2 methods respectively, one is the new method described and the other is pixel duplication. Experimental results show that the new method is good for partial image magnification with no block effect.
Edge detection is important in many fields such as pattern recognition and computer vision. Many edge detection methods are sensitive to noises because gradients are used to enhance edges. To solve this problem, a new edge detection method is proposed in the paper based on local self-similarity. For any pixel in an image, a metric, called as local self-similar coefficient, is defined on its square neighborhood. The square neighborhood blocks are classified into three types: edge block, smooth block and random block. Two theorems have been proven according to the self-similar metric definition and the image block classification. The theorems and experimental results demonstrate that the local self-similar coefficients on edge blocks and smooth blocks are much greater than that on random blocks. Fortunately, it is quite easy to distinguish edge blocks from smooth blocks. A new edge detection algorithm based on these properties is provided in the paper. Several kinds ofimages, including human pictures and natural scenery, are used to detect edges with the new algorithm, and satisfactory results are obtained. The results show that under noisy conditions, the new algorithm extracts better edges than Sobel method.
Motion estimation plays an important role in real-time video coding because it can improve compression efficiency greatly. Block matching algorithms are popular in motion estimation. The full search algorithm is the most obvious and simplistic block matching algorithm, but its high computational cost limits its practical use. Many fast algorithms are constantly proposed. Fast algorithms can greatly reduce the computation by only searching selected positions in the search window. In this paper, several block matching algorithms (including FS, TSS, TDL, and CS) are introduced and compared by compute simulation. Experiment results show that the full search algorithm provides high compression with low distortion, but it costs much time; fast algorithms reduce the computational time significantly while suffer performance loss; the three-step search algorithm is the most practicably algorithm in the fast algorithms.
Digital watermarking has been recently proposed as the mean for property right protection of digital products. In this paper we analyze the self-similarities in detail signals of discrete wavelet transform of the image for the purpose of protecting the copyright of the image. The signature embedded using this method is retrievable only by the mean of protected information. Our studies have shown that the watermarked image has a good quality of image, and such a watermark is difficult to detect and unchangeable without the appropriate user crytogram.
In this paper, a kind of self-similar coefficient (SSC) of the range blocks in an image is defined in Fractal Image Compression scheme. It also is proved that the range blocks in fractal images possess short distance piecewise self- similarity (SDPS). A novel edge detect method is proposed based on SSC and SDPS, and the result show that this method can be used to extract edge of fractal image effectively.
A novel image compression method is proposed, in this paper, based on fractal prediction. The original image is decimated into a smaller image which is encoded with fractal method based on the fact that the smaller the size of an image, the shorter the time of encoding. A fractal prediction is obtained by decoding an image, at a same size as the original image, from the fractal codes of the decimated image. The prediction image is subtracted from the original image to arrive at a difference image, which is encoded based on DCT for error correction. Experimental results show that this algorithm is faster than typical fractal image coding methods, and the reconstructed image have good fidelities to the original image at relatively high compression. This method combines the advantages of fractal coding and JPEG coding together.
It is well known that images can be greatly compressed by exploiting the self-similar redundancies. In this paper, the self-similarities of wavelet transform are analyzed, and it is discovered that corresponding subbands of different scale detail signals are similar. An image coding method is proposed according to this property. The typical self-affirm transform is modified such that it is adapted to DWT coefficient encoding. An adaptive quantization method of the transform parameters s, is given. Firstly, a J-order discrete wavelet transform of the original image, denoted by LL0, is performed. That is, LL is decomposed into LLj + 1, LHj + 1, HL$_j + 1, for 0 <EQ j <EQ J - 1. Secondly, LLJ$. is encoded based on DCT. Thirdly, HL(subscript J LHJ and HHJ are quantized and run- length coded. Fourthly, HLj, LHj and HHj for 1 <EQ j <EQ J - 1, are encoded with modified self- similar transforms. HLj, LHj, and HHj are divided into non-overlapping range blocks. For each range block Ri (epsilon HLj, a domain block Dj (epsilon) HLj + 1, which best matches Rj, is found, and the parameter s1 of the corresponding transform is determined and adaptively quantized. Several kinds of images are compressed with this method. Experimental results demonstrate that this method can compress images significantly while keeping a very good fidelity. Besides, the algorithm is faster than typical fractal image coding methods because less searching is needed.
Proc. SPIE. 3024, Visual Communications and Image Processing '97
KEYWORDS: Image processing algorithms and systems, Signal to noise ratio, Image compression, Image segmentation, Image processing, Computer programming, Image quality, Digital imaging, Fractal analysis, Iterated function systems
Fractal image compression has recently received considerable attention int he literature. In the previously published encoding techniques, an image is usually partitioned into nonoverlapping blocks, and each block is encoded by a self- affirm mapping from a larger block. The fractal code consists of the description of the image partition, along with that of the image transformation defined as the ordered list of block transformation: ((tau) i O <EQ i < N). Each of these block transformations are specified by a set of quantized parameters. With the help of experiment, we discovered the fact that there do exist blocks which have the same transformations are specified by a set of quantized parameters. With the help of experiment, we discovered the fact that there do exist blocks which have the same transformation parameters as the adjacent block transformations. In this paper we propose a region-based transformation that extends the block-based scheme. The concept of the cross search is defined and a search algorithm of finding the region transformations is also given. The results indicate that at the same signal to noise ratio, the region-based system achieves a higher compression ratio over the block-based scheme, and that our algorithm is fast than the block-based system because of less searching.
In this paper we propose a new concept of scale fractal dimension for the fractal characterization. We point out that scale fractal dimension can supply more information and give a more accurate description for fractal in nature than the usual used fractal dimension dose. The variation of scale fractal dimension for different kinds of images is analyzed and a new metric based on scale fractal dimension for edge detection is defined. After that, the algorithm for edge detection based on scale fractal dimension is given and its performances for edge detection are discussed.
In recent years, fractal image compression has been paid great attention because of its potential of high compression ratio. In the previously published encoding techniques, an image is usually partitioned into nonoverlapping blocks, and each block is encoded by a self-affirm mapping from a larger block. A high cost of the searching process is generally needed to encode a block. With the help of experiments, we discovered blocks do exist which cannot be well matched with any larger blocks under self-affirm transform. To encode these kinds of blocks with the present fractal encoding method may result in relatively low fidelity on these blocks. In this paper, we propose a hybrid fractal encoding method based on DCT and self- affirm transforms to improve local fidelity and encoding speed. The concept of short distance piecewise self-similarity (SDPS) is defined. Those blocks possessing SDPS are encoded with near-center self-affirm transform method. Other blocks are encoded with quasi-JPEG algorithm. Our method makes use of both the advantages of fractal coding technique, possessing the potential of high compression ratio, and the advantages of JPEG algorithm providing high fidelity at low or medium compression.