Characterizing the response of charge-couple device digital color cameras

Two-color, two-dimensional pyrometers based on monochrome and color cameras for high-temperature (>1000 K) planar measurements

Review of Scientific Instruments ◽

10.1063/5.0021784 ◽

2020 ◽

Vol 91 (11) ◽

pp. 114901

Author(s):

S. Jiménez

Keyword(s):

High Temperature ◽

Two Dimensional ◽

Color Cameras

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Accurate spectral response measurement system for digital color cameras

10.1117/12.702943 ◽

2007 ◽

Author(s):

Gao-Wei Chang ◽

Zong-Mu Yeh

Keyword(s):

Measurement System ◽

Spectral Response ◽

Response Measurement ◽

Color Cameras

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Charge couple device-based system for 3-dimensional real time positioning on the assessment of segmental range of motion of lumbar spine

Chinese Journal of Integrative Medicine ◽

10.1007/bf02835788 ◽

2005 ◽

Vol 11 (4) ◽

pp. 272-278

Author(s):

Zhao Ping ◽

Chen Li-jun ◽

Guan Jing ◽

Pan Li ◽

Ding Hui ◽

...

Keyword(s):

Lumbar Spine ◽

Range Of Motion ◽

Real Time ◽

Charge Couple Device ◽

3 Dimensional

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Iterative Refinement of Uniformly Focused Image Set for Accurate Depth from Focus

Applied Sciences ◽

10.3390/app10238522 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8522

Author(s):

Sherzod Salokhiddinov ◽

Seungkyu Lee

Keyword(s):

Depth Estimation ◽

Poor Quality ◽

Iterative Refinement ◽

Object Boundary ◽

Depth From Focus ◽

3D Shape ◽

Polynomial Curve ◽

Frequency Domains ◽

Image Set ◽

Color Cameras

Estimating the 3D shape of a scene from differently focused set of images has been a practical approach for 3D reconstruction with color cameras. However, reconstructed depth with existing depth from focus (DFF) methods still suffer from poor quality with textureless and object boundary regions. In this paper, we propose an improved depth estimation based on depth from focus iteratively refining 3D shape from uniformly focused image set (UFIS). We investigated the appearance changes in spatial and frequency domains in iterative manner. In order to achieve sub-frame accuracy in depth estimation, optimal location of focused frame in DFF is estimated by fitting a polynomial curve on the dissimilarity measurements. In order to avoid wrong depth values on texture-less regions we propose to build a confidence map and use it to identify erroneous depth estimations. We evaluated our method on public and our own datasets obtained from different types of devices, such as smartphones, medical, and normal color cameras. Quantitative and qualitative evaluations on various test image sets show promising performance of the proposed method in depth estimation.

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