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Imaging Systems
Published in Takao Kuroda, Essential Principles of Image Sensors, 2017
While defect-free (white and black defects) sensors are desirable, sensor cost would be quite expensive if only perfect zero-defect sensors could be applied for imaging systems. Therefore, sensors having defects within the correctable range of level and number are provided for practical use. To correct the defect, the signal of the defective pixel is substituted by that of another, normal pixel or a signal obtained by peripheral normal pixels. In brightness correction, the signal level is adjusted for easy subsequent processing.
Detector construction
Published in Ross I. Berbeco, Beam’s Eye View Imaging in Radiation Oncology, 2017
Due to inconsistent manufacturing, there are pixels that do not function at all or exhibit unstable behavior. The task of the defective pixel correction function is to replace these defective pixels with an estimated pixel value.
Low-rank flat-field correction for artifact reduction in spectral computed tomography
Published in Applied Mathematics in Science and Engineering, 2023
Katrine Ottesen Bangsgaard, Genoveva Burca, Evelina Ametova, Martin Skovgaard Andersen, Jakob Sauer Jørgensen
Most reconstruction methods rely on the assumption that the detector response is known. In practice, however, the detector response is subject to various errors and must be estimated from measurements acquired without an object in the scanner, i.e. from flat fields, also referred to as air scans [7], white fields [8] or open beams. The flat fields are noisy due to factors such as measurement noise, miscalibration, defective pixel elements with non-linear response, and may introduce concentric rings in the reconstruction, which are known as ring artifacts [9]. Ring artifacts are a great challenge for experimental CT set-ups with low-dose and/or short exposure time [10] and can significantly degrade the quality of the reconstruction. In spectral CT, we measure spectral flat fields, i.e. flat fields for each energy. However, the spectral measurements share the characteristics of low-dose CT since each energy channel has a low signal-to-noise ratio (SNR), and hence ring artifacts present a challenge in spectral CT [11, 12].
An adaptive clustering method detecting the surface defects on linear guide rails
Published in International Journal of Computer Integrated Manufacturing, 2019
Youhang Zhou, Zhuxi Ma, Xuanwei Shi, Kui Zhang
After obtaining the images shown in Figure 4, the similarity matrix of each pixel is constructed using the MPPCA method that uses Eqs. (1)-(5) and the improvement of similarity weight from Eq. (8). Then, using clustering of the local density peaks, clustering centers and numbers are adaptively selected. The threshold of was set as the result of 1/4max multiplied by 1/4max. The information for all defective pixel points is represented in the plane, as shown in Figure 5.
CMOS Implementation of Time Delay Integration (TDI) for Imaging Applications: A Brief Review
Published in IETE Technical Review, 2020
Sushil Kumar Semwal, Raghvendra Sahai Saxena
In 2002, Tsai et al. [8] had used TDI approach in CMOS read out integrated circuit (ROIC) for infrared focal plane array (IRFPA). With the help of this method they were able to increase the integration time per pixel and thus the Signal to Noise Ratio. The other major advantage was the feasibility of implementing a processing circuit in CMOS, which was used to add additional feature of defective pixel removal. Thus the effect of faulty pixels was reduced in overall image. Figure 4 shows their reported TDI readout circuit for one unit cell.