New Direct Color Mapping Method for Reducing the Storage Capacity of Look-Up Table Memory

1989 ◽  
Author(s):  
Hiroaki Ikegami
Keyword(s):  
Storage Capacity ◽  
Mapping Method ◽  
Color Mapping ◽  
Look Up Table ◽  
Direct Color

scholarly journals A MAPPING METHOD OF SLAM BASED ON LOOK UP TABLE

2017 ◽  
Vol IV-2/W4 ◽  
pp. 407-410
Author(s):  
Z. Wang ◽  
J. Li ◽  
A. Wang ◽  
J. Wang
Keyword(s):  
Mapping Method ◽  
Good Choice ◽  
Feature Points ◽  
Key Frame ◽  
Whole Process ◽  
Look Up Table ◽  
Localization And Mapping ◽  
Tracking Direction ◽  
The Look ◽  
First Time

In the last years several V-SLAM(Visual Simultaneous Localization and Mapping) approaches have appeared showing impressive reconstructions of the world. However these maps are built with far more than the required information. This limitation comes from the whole process of each key-frame. In this paper we present for the first time a mapping method based on the LOOK UP TABLE(LUT) for visual SLAM that can improve the mapping effectively. As this method relies on extracting features in each cell divided from image, it can get the pose of camera that is more representative of the whole key-frame. The tracking direction of key-frames is obtained by counting the number of parallax directions of feature points. LUT stored all mapping needs the number of cell corresponding to the tracking direction which can reduce the redundant information in the key-frame, and is more efficient to mapping. The result shows that a better map with less noise is build using less than one-third of the time. We believe that the capacity of LUT efficiently building maps makes it a good choice for the community to investigate in the scene reconstruction problems.

A Color Mapping Method for Decimated Model

2014 ◽  
pp. 83-93
Author(s):  
Bo Yu ◽  
Maria Savchenko ◽  
Luis Diago ◽  
Junichi Shinoda ◽  
Ichiro Hagiwara
Keyword(s):  
Mapping Method ◽  
Color Mapping

scholarly journals Improving Color Space Conversion for Camera-Captured Images via Wide-Gamut Metadata

2020 ◽  
Vol 2020 (28) ◽  
pp. 193-198
Author(s):  
Hoang Le ◽  
Mahmoud Afifi ◽  
Michael S. Brown
Keyword(s):  
Color Space ◽  
Mapping Function ◽  
Mapping Method ◽  
Color Spaces ◽  
Color Gamut ◽  
Color Mapping ◽  
Color Space Conversion ◽  
Different Color ◽  
Image Format ◽  
Image State

Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.

A novel color mapping method for preferred color reproduction

2007 ◽  
Author(s):  
Kyeong Man Kim ◽  
Hyun Soo Oh ◽  
Sang Ho Kim ◽  
Don Chul Choi
Keyword(s):  
Mapping Method ◽  
Color Reproduction ◽  
Color Mapping

Chemical-shift analysis of O Kα by EPMA color-mapping method for BiSrCaCuO superconductive specimen

1992 ◽  
Vol 50 (1) ◽  
pp. 82-83
Author(s):  
H. Takahashi ◽  
T. Okumura ◽  
Y. Seo ◽  
A. Kabaya ◽  
C. Nielsen
Keyword(s):  
Chemical Shift ◽  
Crystal Structures ◽  
Chemical Shifts ◽  
Mapping Method ◽  
Color Mapping ◽  
Shift Analysis ◽  
Spectral Peaks ◽  
Sintering Method ◽  
Chemical Shift Analysis ◽  
Acid Phthalate

The chemical shifts of x-ray spectra are now frequently observed with EPMA (Electron Probe Microanalysis). The conventional method of chemical-shift analysis with EPMA is to compare the peak shapes and peak positions of standard spectra with those of unknown spectra. We reported that O-Kα peak shapes detected by using a TAP (Thallium acid phthalate) crystal reflect their crystal structures. Fig. 1 shows these O-Kα spectral peaks. In the present study, concerning the BiSrCaCuO superconductor made by the sintering method, it was observed that the O-Kα spectra of several kinds of phases reflected their crystal structures. Moreover, it is now possible to observe these chemical shifts of spectra by using the color mapping method in EPMA.

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

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