• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2003.11a
• /
• pp.47-50
• /
• 2003

본 논문에서는 동영상을 효율적으로 부호화하기 위한 새로운 다중해상도 움직임 보상 방법과 잉여 양자화 방법을 제안한다. 본 논문에서 제안하는 동영상 부호화기는 다단계 이산웨이브렛 분해 움직임 예측 및 움직임 보상 블록 Tree 의 구성 및 블록 분할. 적응적 산술 부호화기로 구성된다 제안된 동영상 부호화기는 단순하면서도 낮은 연산량을 필요로 하며, 임베디드 특성과 SNR 계위 부호화 특성과 같은 좋은 기능을 제공한다. 또한 기존에 제안되었던 이산웨이브렛변환을 이용하는 동영상 부호화 방법과 비교하여 우수한 성능을 제공한다.

• Journal of the Korean earth science society
• /
• v.32 no.6
• /
• pp.575-585
• /
• 2011

The effect of wavelet pair choice in the compression of the satellite images is studied. There is a trade-off between compression rate and perception quality. The encoding ratio is used to express the compression rate, and Peak Signal-to-Noise Ratio (PSNR) is also used for the perceptional performance. The PSNR and the encoding ratio are not matched well for the images with various wavelet pairs, but the tendency is remarkable. It is hard to find the pattern of PSNR for sampled images. On the other hand, there is a pattern of the variation range of the encoding ratio for each image. The satellite images have larger values of the encoding ratio than those of nature images (close range images). Depending on the wavelet pairs, the PSNR and the encoding ratio vary as much as 13.2 to 21.6% and 16.8 to 45.5%, respectively for each image. For Synthetic Aperture Radar (SAR) images the encoding ratio varies from 16 to 20% while for the nature images it varies more than 40% depending on the choice of wavelet pairs. The choice of wavelet for the compression affects the nature images more than the satellite images. With the indices such as the PSNR and the encoding ratio, the satellite images are less sensitive to the choice of wavelet pairs. A new index, energy concentration ratio (ECR) is proposed to investigate the effect of wavelet choice on the satellite image compression. It also shows that the satellite images are less sensitive than the nature images. Nevertheless, the effect of wavelet choice on the satellite image compression varies at least 10% for all three kinds of indices. However, the important of choice of wavelet pairs cannot be ignored.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.4
• /
• pp.14-23
• /
• 2005

This paper proposes a method for matching two different images, especially satellite images. In the general image matching fields, when an image is compared to other image, they may have different properties on the size, contents, brightness, etc. If there is no noise in each image, in other words, they have identical pixel level and unchanged edges, the image matching method will be simple comparison between two images with pixel by pixel. However, in many applications, most of images to be matched should have much different properties. This paper proposes an efficient method for matching satellite images. This method is to match a raw satellite image with GCP chips. From this we can make a geometrically corrected image. The proposed method is based on wavelet transformation, not required any pre-processing such as histogram equalization, analysis of raw image like the traditional methods.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.37 no.3
• /
• pp.45-55
• /
• 2000

In this paper, we proposed the hardware architecture of wavelet transform digital filter for an image processing. Filter bank pyramid algorithm is used for wavelet transform and each fillet is implemented by the FIR filter. For DWT computation, because the memory controller is implemented by hardware, we can efficiently process the multisolution decomposition of the image data only input the parameter. As a result of the image Processing in this paper, 33㏈ PSNR has been obtained on 512$\times$512 B/W image due to 11-bit mantissa processing in FPGA Implementation. And because of using QMF( Quadrature Mirror Filter) properties, it reduces half number of the multiplier needed DWT(Discrete Wavelet Transform) computation so the hardware size is reduced largely. The proposed scheme can increase the efficiency of an image Processing as well as hardware size reduced. The hardware design proposed of DWT fillet bank is synthesized by VHDL coding and then the test board is manufactured, the operating Program and the application Program are implemented using MFC++ and C++ language each other.

• The Journal of the Acoustical Society of Korea
• /
• v.15 no.5
• /
• pp.21-29
• /
• 1996

Industrial equipment, such as power plant, is required to operate reliably, continuously and economically under rather severe conditions of temperature, stress, and enbironment. To test structural integrity and fitness, ultrasonic nondestructive testing is used because of effectiveness and simplicity. In this paper, wavelet transform based least mean square(LMS) algorithm is applied to reduce the influence of the interference occurring between randomly positioned small scatters. The RUN test is performed to check the nonstationarity of the speckle noise signal. The performance of this new approach is compared with that of the time domain LMS algorithm by means of condition numbers, signal-to-noise ratio and 3-D image. As a result, the wavelet transform based LMS algorithm shows better performance than the time domain LMS algorithm in this experiment.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.37 no.3
• /
• pp.104-113
• /
• 2000

In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.12
• /
• pp.67-75
• /
• 1999

In this paper, we present an ASIC(Application Specific Integrated Circuit) design of wavelet transform filter Wavelet transform is used in lots of application fields which include image compression, because it has an excellent energy compaction. The operation characteristic and performance of wavelet transform filter are analyzed by using verilog-HDL(Hardware Description Language). In this paper, the designed wavelet transform filter uses line memory to improve data processing rate. Generally, when it reads and writes data of DRAM by using Fast Page Mode, input and output processing is very fast in horizontal direction but substantially slow in vertical direction. The use of line memory solves this low speed processing problem. As a result, though the size of the chip is getting larger, processing time for an image frame becomes 4.66ms. Generally, since the limit of 1 frame processing time on the data of TV video is 33ms, so it is appropriate for TV video.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.3
• /
• pp.143-148
• /
• 2007

The many studies have been proceeding to express accurately the feature of a sudden signal and a uncertain system in the image processing field. It is well know that Fourier Transform is widely used for frequency analysis of any signal. However, The frequency transform domain is not used for expressing the sudden signal change and non-stationary signal at the time-axis by this method. This paper describes of image analysis by discrete wavelet transform. Wavelet modulus maxima on transformed plane gives the Lipschitz exponent expression, which is useful to examine the characteristics of signal or the edge of an image. It is possible to reconstruct the original image only using the few maxima points. The fractal analysis is applied as an examples. The visualized image of oil flow on a ship model is analyzed. The fractal variable is obtained by the maxima analysis and the good results on the exprement is obtained by the visualized image analysis.

• Journal of the Institute of Convergence Signal Processing
• /
• v.11 no.2
• /
• pp.157-162
• /
• 2010

In this paper we propose a fractal analysis based on the discrete wavelet transform. It is well known that Fourier Transform is widely used for frequency analysis of random signal. However, the frequency domain is not used for expressing the sudden signal change and non-stationary signal at the time-axis by this method. Maximum value in the wavelet modules can be expressed by the Lipschitz exponent, which is useful to represent the characteristics of signal or the edge of an image. It is possible to reconstruct the original image only by using the few maximum points. The v possible image It iusing oil was acquired to interpret the maximum value. ufter that, it was applied to the v possible image of a ship model. In addition, the fractal dimens by by the conlapse process of the sediment particle was examined. In this paper, the fractal dimens by has been obtained by the maximum value and the experiment obtained from the visualized image also acquired the same result as existing methods.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.5
• /
• pp.462-470
• /
• 2002

Wideband speech, characterized by a bandwidth of 50∼7000 ㎐, sounds more natural and intelligible, and is less tiring to listen to when compared to narrowband speech characterized by a bandwidth of 300∼3400 ㎐. Wideband speech coders, however, have not been as successful as the narrowband speech coders because of their higher bit rate. In this paper, we propose a new wideband speech coder which combines the European standard of a narrowband speech coder, i.e., GSM-EFR, and a transform coder using the discrete wavelet transform. The proposed wideband speech coder operates as follows input speech is first split into two subbands with equal bandwidth and the two subband signals are coded and decoded by each subband coder. A GSM-EFR is adopted as a lower subband coder and a subband coder with wavelet transformed speech is designed for a upper subband coder. The total bit rate of the proposed coder is 18.9kbps (12.2 kbps for lower band coder and 6.7 kbps for upper band coder), and informal listening test results have shown that the proposed coder has comparable speech quality to that of G.722 with 56 kbps.