Results: Integrating the Supersaturated Material in a CMOS Pixel Matrix

Abstract X-ray imaging of moving objects using line detectors remains the most popular method of object content and structure examination with a typical resolution limited to 0.4–1 mm. Higher resolutions are difficult to obtain as, for the detector in the form of a single pixel row, the narrower the detector is, the lower the image Signal to Noise Ratio (SNR). This is because, for smaller pixel sizes, fewer photons hit the pixel in each time unit for a given radiation intensity. To overcome the trade-off between the SNR and spatial resolution, a two-dimensional sensor, namely a pixel matrix can be used. Imaging of moving objects with a pixel matrix requires time-domain integration (TDI). Straightforward TDI implementation is based on the proper accumulation of images acquired during consecutive phases of an object’s movement. Unfortunately, this method is much more demanding regarding data transfer and processing. Data from the whole pixel matrix instead of a single pixel row must be transferred out of the chip and then processed. The alternative approach is on-chip TDI implementation. It takes advantage of photons acquired by multiple rows (a higher SNR), but generates similar data amount as a single pixel row and does not require data processing out of the chip. In this paper, on-chip TDI is described and verified by using a single photon counting two-dimensional (a matrix of 128 × 192 pixels) CdTe hybrid X-ray detector with the 100 µm × 100 µm pixel size with up to four energy thresholds per pixel. Spatial resolution verification is combined with the Material Discrimination X-ray (MDX) imaging method.

Download Full-text

Based on the Law of Bill Traversal of Underwater Optical Image Restoration Algorithm for Color Pixel Matrix

Communications in Computer and Information Science - Advances in Wireless Sensor Networks ◽

10.1007/978-3-642-54522-1_33 ◽

2014 ◽

pp. 337-344

Author(s):

Hao Xu ◽

Bing Zheng ◽

Tingting Lin

Keyword(s):

Image Restoration ◽

Optical Image ◽

Restoration Algorithm ◽

The Law ◽

Color Pixel ◽

Pixel Matrix

Download Full-text

A New Position Feedback Method for Manufacturing Equipment

ASME 2008 International Manufacturing Science and Engineering Conference, Volume 1 ◽

10.1115/msec_icmp2008-72222 ◽

2008 ◽

Cited By ~ 2

Author(s):

Chan Wong ◽

Carlos Montes ◽

Laine Mears ◽

John Ziegert

Keyword(s):

Digital Images ◽

Liquid Crystal Display ◽

Digital Camera ◽

Position Sensing ◽

Test Platform ◽

Position Feedback ◽

Feedback Method ◽

Future Work ◽

Pixel Matrix ◽

Noise Reduction Algorithm

This paper presents an innovative real time 2-dimensional position feedback method, which processes visual input data from a target image on an actively-controlled planar pixel matrix. The objective is to demonstrate the ability to position an X-Y stage with high resolution, using direct position sensing of a dynamically controlled image. In order to achieve high spatial resolution using a pixel array as a target, an algorithm that processes both the geometric shape and the grayscale intensities of the image is implemented. The test platform consists of an X-Y stage carrying a Liquid Crystal Display (LCD) screen that is imaged by a stationary digital camera. The pixel intensities on the LCD screen are modified dynamically to provide 2-dimensional position command inputs that translate to the desired stage motion. The digital images acquired by the camera are used to provide position error feedback to the controller. Experimental results show that direct position sensing is possible to a certain degree of accuracy. However, in order to match today’s CNC machines’ accuracy levels further processing of the digital images is required. A noise reduction algorithm to filter the fluctuations of the measurements in the digital images is proposed as future work, as well as other considerations.

Download Full-text

Acquisition and processing of multiparametric information from a pixel matrix

IEEE Transactions on Nuclear Science ◽

10.1109/23.958759 ◽

2001 ◽

Vol 48 (4) ◽

pp. 1244-1248 ◽

Cited By ~ 2

Author(s):

P.F. Manfredi ◽

J.E. Millaud ◽

V.V. Sushkov

Keyword(s):

Pixel Matrix

Download Full-text

TFT-Directed Electroplating of RGB Luminescent Films without a Vacuum or Mask toward a Full-Color AMOLED Pixel Matrix

ACS Applied Materials & Interfaces ◽

10.1021/acsami.8b04487 ◽

2018 ◽

Vol 10 (21) ◽

pp. 17519-17525 ◽

Cited By ~ 10

Author(s):

Rong Wang ◽

Donglian Zhang ◽

You Xiong ◽

Xuehong Zhou ◽

Cao Liu ◽

...

Keyword(s):

Full Color ◽

Luminescent Films ◽

Pixel Matrix

Download Full-text

Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers

Applied Sciences ◽

10.3390/app10020628 ◽

2020 ◽

Vol 10 (2) ◽

pp. 628

Author(s):

Di Lv ◽

Yong Zhang ◽

Jiongbin Lin ◽

Peiyuan Wan ◽

Yongli Hu

Keyword(s):

Travel Time ◽

Public Transportation ◽

Travel Behavior ◽

Visual Exploration ◽

Passenger Travel ◽

Working Together ◽

Transport Safety ◽

Abnormal Behaviors ◽

The Relationship ◽

Pixel Matrix

More and more people in mega cities are choosing to travel by public transportation due to its convenience and punctuality. It is widely acknowledged that there may be some potential associations between passengers. Their travel behavior may be working together, shopping together, or even some abnormal behaviors, such as stealing or begging. Thus, analyzing association between passengers is very important for management departments. It is very helpful to make operational plans, provide better services to passengers and ensure public transport safety. In order to quickly explore the association between passengers, we propose a multi-view interactive exploration method that provides five interactive views: passenger 3D travel trajectory view, passenger travel time pixel matrix view, passenger origin-destination chord view, passenger travel vehicle bubble chart view and passenger 2D travel trajectory view. It can explore the associated passengers from multiple aspects such as travel trajectory, travel area, travel time, and vehicles used for travel. Using Beijing public transportation data, the experimental results verified that our method can effectively explore the association between passengers and deduce the relationship.

Download Full-text