• 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.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.727-731
• /
• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

• 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.

• The Bulletin of The Korean Astronomical Society
• /
• v.36 no.1
• /
• pp.59.1-59.1
• /
• 2011

We report the HST pixel analysis results of the interacting S0 galaxy, NGC 5195 (M51B), using the HST/ACS images in the F435W, F555W and F814W (BVI) bands. After 4x4 binning of the HST/ACS images to secure sufficient signal-to-noise ratio for each pixel, we derive several quantities describing the pixel color-magnitude diagram (pCMD) of NGC 5195, such as blue/red color cut, red pixel sequence parameters, blue pixel sequence parameters and blue-to-red pixel ratio. Those parameters reflect the internal properties of NGC 5195 like age, metallicity, dust content and galaxy morphology. To investigate the spatial distributions of stellar populations, we divide pixel stellar populations using the pixel color-color diagram and population synthesis models. As a result, we find that the tidal interaction with NGC 5194 significantly affects the stellar populations in their dust content and mean stellar age.

• Current Optics and Photonics
• /
• v.4 no.5
• /
• pp.428-433
• /
• 2020

Recently, the on-chip autofocus (AF) function has become essential to the CMOS image sensor. An auto-focus usually operates using phase detection of the photocurrent difference from a pair of AF pixels that have focused or defocused. However, the phase-detection method requires a pair of AF pixels for comparison of readout. Therefore, the pixel variation may reduce AF performance. In this paper, we propose a color-selective AF pixel with a plasmonic nanostructure in a 0.9 μ㎡ pixel. The suggested AF pixel requires one pixel for AF function. The plasmonic nanostructure uses metal-insulator-metal (MIM) stack arrays instead of a color filter (CF). The color filters are formed at the subwavelength, and they transmit the specific wavelength of light according to the stack period and incident angles. For the optical analysis of the pixel, a finite-difference time-domain (FDTD) simulation was conducted. The analysis showed that the MIM stack arrays in the pixels perform as an AF pixel. As the primary metric of AF performance, the resulting AF contrasts are 1.8 for the red pixels, 1.6 for green, and 1.5 blue. Based on the simulation results, we confirmed the autofocusing performance of the MIM stack arrays.

• 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 Korea Institute of Information and Communication Engineering
• /
• v.15 no.6
• /
• pp.1363-1368
• /
• 2011

This paper describes an analysis on the granular noise in pixel-to-pixel mapping-based computational integral imaging. The pixel mapping-based method provides a high-resolution reconstructed images and also its computational cost is very lower than the previous back-projection-based method. In this paper, a signal model for the pixel mapping-based method is introduced, which defines and analyzes the granular noise. Computer experiments provides the granular noise properties based on the proposed signal model. The experimental results indicates that the granular noise pattern differs from that of the back-projection based method. The results is also utilized in the pixel mapping-based method.

• 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.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.20 no.3
• /
• pp.250-256
• /
• 2007

We analyzed the effect of a pixel and all the inter-electrode capacitances in a unit pixel of TFT-LCDs on the gray scale capability. The pixel and all the inter-electrode parasitic capacitances were obtained from the tree dimensional profiles of potential distribution and molecular director considering lateral fields generated at the edge of the pixel. To obtain the RMS and kickback voltages of the pixel, we constructed an equivalent circuit of the panel containing all the parasitic capacitances. The calculation was performed though H-SPICE. As results, we confirmed that the pixel becomes smaller, the effect of parasitic capacitances on the gray scale capability becomes larger.

• 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.