• Korean Journal of Geomatics
• /
• v.4 no.1
• /
• pp.1-8
• /
• 2004

In the middle-resolution remote sensing, the Ground Sampled Distance (GSD) that the detector senses and samples is generally larger than the actual size of the objects (or materials) of interest, and so several objects are embedded in a single pixel. In this case, as it is impossible to detect these objects by the conventional spatial-based image processing techniques, it has to be carried out at sub-pixel level through spectral properties. In this paper, we explain the sub-pixel analysis algorithm, also known as the Linear Spectral Mixing (LSM) model, which has been experimented using the Hyperion data. To find Endmembers used as the prior knowledge for LSM model, we applied the concept of the convex geometry on the two-dimensional scatter plot. The Atmospheric Correction and Minimum Noise Fraction techniques are presented for the pre-processing of Hyperion data. As LSM model is the simplest approach in sub-pixel analysis, the results of our experiment is not good. But we intend to say that the sub-pixel analysis shows much more information in comparison with the image classification.

• 한국가시화정보학회:학술대회논문집
• /
• 2001.12a
• /
• pp.14-22
• /
• 2001

The frequency responses on the sub-pixel evaluation technique were investigated using the Monte-calro Simulation technique. The frequency response by the FFT based cross-correlation gives very good results, however, the gain loss does exist for the small displacement, (less than 0.5 pixel). While, the no gain loss is observed in the Direct Cross-correlation, however, the sub-pixel accuracy was limited to be about 0.1 pixel, i.e., it could not detect the small displacement. To detect the higher accurate sub-pixel displacement, the gradient based technique is the best. For the small interrogation area (e.g., 4x4), only the gradient technique can detect the small displacement correctly.

• Korean Journal of Remote Sensing
• /
• v.31 no.4
• /
• pp.303-319
• /
• 2015

The objectives of this paper are to measure surface imperviousness using three different classification methods: per-pixel, sub-pixel, and object-oriented classification. They are tested on high-spatial resolution QuickBird data at 2.4 meters (four spectral bands and three principal component bands) as well as a medium-spatial resolution Landsat TM image at 30 meters. To measure impervious surfaces, we selected 30 sample sites with different land uses and residential densities across image representing the city of Phoenix, Arizona, USA. For per-pixel an unsupervised classification is first conducted to provide prior knowledge on the possible candidate spectral classes, and then a supervised classification is performed using the maximum-likelihood rule. For sub-pixel classification, a Linear Spectral Mixture Analysis (LSMA) is used to disentangle land cover information from mixed pixels. For object-oriented classification several different sets of scale parameters and expert decision rules are implemented, including a nearest neighbor classifier. The results from these three methods show that the object-oriented approach (accuracy of 91%) provides more accurate results than those achieved by per-pixel algorithm (accuracy of 67% and 83% using Landsat TM and QuickBird, respectively). It is also clear that sub-pixel algorithm gives more accurate results (accuracy of 87%) in case of intensive and dense urban areas using medium-resolution imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.15 no.2
• /
• pp.245-252
• /
• 1997

The development of digital camera and advancement of computer processor could simplify the acquisition and the analysis of digial image, and be the real-time processing by the digital photogrammetry. This study is about to enhancement of the image measuring accuracy by the centroid methods. We were able to determine more effective centroid measuring methods and suitable target shape as the development of analysis system and actualize semi-automatic measuring of digital image. And we can supply the weakness of non-metric camera for the geometric internal accuracy of digital image as the correct of Kodak DCS200 camera 8008s lens distortion.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2009.10a
• /
• pp.443-446
• /
• 2009

In this paper, an accurate ray-tracing based visual analysis method of lenticular 3D liquid liquid crystal display (LCDs) and some analysis results are presented. In the developed method, the geometric optics analysis is performed on the single 3D unit pixel of 3D lenticular LCD. It is shown that the display characteristics of 3D lenticular LCD panels of arbitrary size can be evaluated through the 3D unit pixel analysis. The analysis results of a few representative structures of 3D lenticular LCDs are compared.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.21 no.4
• /
• pp.368-375
• /
• 2008

In this paper, we calculated the pixel and all the inter-electrode capacitances in a unit pixel of three kinds of TFT-LCD modes in order to realize the full color image. And we analyzed the effect on applied voltage. We fixed size of sub-pixel and designed a unit pixel of three kinds of TFT-LCD modes. We calculated rigorously the pixel and all the inter-electrode capacitances by the three dimensional simulation. And we expanded one pixel into whole panel using H-SPICE. As a result, we calculated the RMS voltage and kickback voltage which most affect gray scale of the pixel and calculated the number of bit according to permissible range of minimum gray scale using V-T curve.

• Ocean Systems Engineering
• /
• v.2 no.2
• /
• pp.137-145
• /
• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Journal of Sensor Science and Technology
• /
• v.17 no.1
• /
• pp.41-52
• /
• 2008

In this paper, a circuit analysis of the complementary CMOS active pixel and readout circuit is carried out. Complementary pixel structure which is different from conventional 3TR APS structure is consist of photo diode, reset PMOS, several NMOSs and PMOSs sets for complementary signals. Photo diode is modelled with Medici device program. HSPICE was used to analyze the variation of the signal feature depending on light intensity using $0.5{\mu}M$ standard CMOS process. Simulation results show that the output signal range is from 0.8 V to 4.5 V. This signal range increased 135 % output dynamic range compared to conventional 3TR pixel in the condition of 5 V power supply.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.2
• /
• pp.164-173
• /
• 2013

In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.343-348
• /
• 1998

In this study, we extracted several terrain information using satellite and aerial images. We detected change of terrain using Landsat Thematic Mapper(TM) and aerial images which are multitemporal data. In change detection processing, we first classified satellite images by ISODATA algorithm which is an unsupervised learning algorithm, then performed change detection. By this method, we could obtain good result. Also we introduce sub-pixel concept to classify road and agriculture area in inaccessible area. In summary, in chang detection processing, we can find that the used method is efficient.