• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.49-62
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• 1994

Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2543-2551
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• 1997

This paper proposes a compression technique of image data, a variable length PN code and channel models which are required in CDMA communication system. It also analyzes their performances. Original images is compressed by 2-D DCT and its coefficients are quantized by optimal quantizer at compression rate 0.84bit/pel. Channel model 1 and 2 which are composed of 5 and 4 channels respectively are employed to be used in CDMA. Such a situation forces us to empoly variable length PN code, such as Chebyshev map for spread spectrum system. When average PN code length of model 1 and 2 is 44.4 and 26.7 chips respectively, the received image through these models under Gaussian noise with variance 1.75 is visually of the same quality as the transmitting image. Thus, the model 2 appears to be better in channel efficiency, comparing with channel model 1 and channel model which uses fixed length PN code.

• Publications of The Korean Astronomical Society
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• v.12 no.1
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• pp.185-196
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• 1997

We present a code which identifies individual clouds in crowded region using IMFORT interface within Image Reduction and Analysis Facility (IRAF). We define a cloud as an object composed of all pixels in longitude, latitude, and velocity that are simply connected and that lie above some threshold temperature. The code searches the whole pixels of the data cube in efficient way to isolate individual clouds. Along with identification of clouds it is designed to estimate their mean values of longitudes, latitudes, and velocities. In addition, a function of generating individual images (or cube data) of identified clouds is added up. We also present identified individual clouds using a $^{12}CO$ survey data cube of Galactic Anticenter Region (Lee et al. 1997) as a test example. We used a threshold temperature of $5\sigma$ rms noise level of the data With a higher threshold temperature, we isolated subclouds of a huge cloud identified originally. As the most important parameter to identify clouds is the threshold value, its effect to the size and velocity dispersion is discussed rigorously.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.1-8
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• 2017

Naive Bayes nearest neighbor (NBNN) is a simple image classifier based on identifying nearest neighbors. NBNN uses original image descriptors (e.g., SIFTs) without vector quantization for preserving the discriminative power of descriptors and has a powerful generalization characteristic. However, it has a distinct disadvantage. Its memory requirement can be prohibitively high while processing a large amount of data. To deal with this problem, we apply a spherical hashing binary code embedding technique, to compactly encode data without significantly losing classification accuracy. We also propose using an inverted index to identify nearest neighbors among binarized image descriptors. To demonstrate the benefits of our method, we apply our method to two existing NBNN techniques with an image dataset. By using 64 bit length, we are able to reduce memory 16 times with higher runtime performance and no significant loss of classification accuracy. This result is achieved by our compact encoding scheme for image descriptors without losing much information from original image descriptors.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.537-539
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• 2007

Telemetry processing system requires minimum bit transition level in data streams to maintain a bit synchronization while receiving telemetry signal. PN code has a capability of providing the bit transition and is widely used in the packet communication of CCSDS. CCSDS PN code that generator polynomial is $h(x)=x^{8}+x^{7}+x^{5}+x^{3}+1$, and the random bit sequence that is generated from this polynomial is repeated with the cycle of 255 bits. As the resolution of satellite image increases, the size and transmission rate of data increases. To process of huge and bulky size of satellite image, the speed of CCSDS PN Processing is very important. This paper introduces the way of improving the CCSDS PN Processing speed through processing 128 bits at one time using the feature of cyclic structure that repeats after first 255 bytes by grouping the random bit sequence with 1 byte and Intel Streaming SIMD Extensions 2. And this paper includes the comparison data of processing speed between SSE2-applied implementation and not-applied implementation, in addition, the measured value of speed improvement.

• Journal of Information Processing Systems
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• v.6 no.4
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• pp.435-452
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• 2010

This paper proposes a novel reversible data hiding scheme based on a Vector Quantization (VQ) codebook. The proposed scheme uses the principle component analysis (PCA) algorithm to sort the codebook and to find two similar codewords of an image block. According to the secret to be embedded and the difference between those two similar codewords, the original image block is transformed into a difference number table. Finally, this table is compressed by entropy coding and sent to the receiver. The experimental results demonstrate that the proposed scheme can achieve greater hiding capacity, about five bits per index, with an acceptable bit rate. At the receiver end, after the compressed code has been decoded, the image can be recovered to a VQ compressed image.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.73-82
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• 2022

This paper shows the hiding process of unlimited secret text size in an image using three methods: the first method is the traditional method in steganography that based on the concealing the binary value of the text using the least significant bits method, the second method is a new method to hide the data in an image based on Exclusive OR process and the third one is a new method for hiding the binary data of the text into an image (that may be grayscale or RGB images) using Exclusive and Huffman Coding. The new methods shows the hiding process of unlimited text size (data) in an image. Peak Signal to Noise Ratio (PSNR) is applied in the research to simulate the results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.231-240
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• 2017

This paper aims to study a method to estimate precise carbon absorption by quantification of forest information that uses accurate LiDAR data, hyperspectral image. To estimate precise carbon absorption value by using spatial data, a problem was found out of carbon absorption value estimation method with statistical method, which is already existed method, and then offered optimized carbon absorption estimation method with spatial information by analyzing with methods of compare digital aerial photogrammetry and LiDAR data. It turned out possible Precise classification and quantification in case of using LiDAR and hyperspectral image. Various classification of tree species was possible with use of LiDAR and hyperspectral image. Classification of hyperspectral image was matched in general with field survey and Mahalanobis distance classification method. Precise forest resources could be extracted using high density LiDAR data. Compared with existing method, 19.7% in forest area, 19.2% in total carbon absorption, 0.9% in absorption per unit area of difference created, and improvement was found out to be estimated precisely in international code.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.501-506
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• 2000

Many research in Robot control has effectively proceeded on the development of Aritficial Intelligence Robot which is able to apply to the uncertain and monotonous operations which are repeated continuously in the industrial field. In this study, the precise shape recognition of base metal for welding was gained by mono CCD camera, and the gained data was transformed into Decimal code through Image Board in computer. And the Fuzzy Logic control system designed by use of Fuzzy rule was built to judge whether the base metals were precisely matched or not with Decimal code. Machanically manipulated Robot syst em was linked to Fuzzy Control system through image information, and ultimately, these systems will be able to apply for production system.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.19-34
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• 2005

The difficulties in implementing of image processing algorithms are a major reason for the lack of research into algorithm comparison. This fact makes an image processing research with difficult. We conclude that it is important to represent algorithms in form of reusable code. Since current image processing systems do not fulfill all requirements we must pose on reusable implementations, we propose to solve the reuse problem by applying generic programming. We define two dimensional iterators, which mediate between image processing algorithms and their underlying data structures, so that the same algorithm implementation can be applied to any number of different image formats. The elegance and efficiency of this approach is illustrated by a number of useful examples and demonstrated by porting in existing image processing algorithm IDE(Integrated Development Environment).