Sensor Noise Modeling Using The Skellam Distribution Application To The Color Edge Detection

• doi: 10.1109/CVPR.2007.383004
• title: Sensor noise modeling using the Skellam distribution: Application to the color edge detection
• publisher: IEEE
• isbn: 1-4244-1180-7
• issn: 1063-6919
• partnum: 07CH37898
• rank: 3522
• access_type: LOCKED
• content_type: Conferences
• abstract: In this paper, we introduce the Skellam distribution as a sensor noise model for CCD or CMOS cameras. This is derived from the Poisson distribution of photons that determine the sensor response. We show that the Skellam distribution can be used to measure the intensity difference of pixels in the spatial domain, as well as in the temporal domain. In addition, we show that Skellam parameters are linearly related to the intensity of the pixels. This property means that the brighter pixels tolerate greater variation of intensity than the darker pixels. This enables us to decide automatically whether two pixels have different colors. We apply this modeling to detect the edges in color images. The resulting algorithm requires only a confidence interval for a hypothesis test, because it uses the distribution of image noise directly. More importantly, we demonstrate that without conventional Gaussian smoothing the noise model-based approach can automatically extract the fine details of image structures, such as edges and corners, independent of camera setting.
• article_number: 4270029
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4270029
• html_url: https://ieeexplore.ieee.org/document/4270029/
• abstract_url: https://ieeexplore.ieee.org/document/4270029/
• publication_title: 2007 IEEE Conference on Computer Vision and Pattern Recognition
• conference_location: Minneapolis, MN, USA
• conference_dates: 17-22 June 2007
• publication_number: 4269955
• is_number: 4269956
• publication_year: 2007
• publication_date: 17-22 June 2007
• start_page: 1
• end_page: 8
• citing_paper_count: 36
• citing_patent_count: 0
• download_count: 741
• insert_date: 20070716
• index_terms:
  • ieee_terms:
    • Colored noise
    • Image edge detection
    • Semiconductor device modeling
    • Cameras
    • Charge coupled devices
    • CMOS image sensors
    • Charge-coupled image sensors
    • Optoelectronic and photonic sensors
    • Color
    • Testing
  • dynamic_index_terms:
    • Edge Detection
    • Noise Model
    • Sensor Noise
    • Skellam Distribution
    • Confidence Interval
    • CCD Camera
    • Charge-coupled Device
    • Differences In Intensity
    • Differences In Volume
    • Poisson Distribution
    • Poissonian
    • Pixel Intensity
    • Spatial Domain
    • Image Noise
    • Gaussian Blur
    • Gaussian Smoothing
    • Temporal Domain
    • Noise Distribution
    • Dark Pixels
    • Normal Distribution
    • Gaussian Distribution
    • Gaussian Kernel
    • Gaussian Function
    • Single Image
    • Sample Mean
    • Homogeneous Color
    • Color Homogeneity
    • Canny Edge Detection
    • Non-maximum Suppression
    • Dominant Noise
    • Scene Changes
    • Number Of Images
    • Consecutive Images
    • Large Number Of Images
    • Camera Images
• isbn_formats:
  • format: CD, value: 1-4244-1180-7, isbnType: Historical
  • format: Print ISBN, value: 1-4244-1179-3, isbnType: Historical
• authors:
  • Author Name: Youngbae Hwang
    Affiliation: Department of Electrical Engineering, KAIST, Daejeon, South Korea
    Author URL: https://ieeexplore.ieee.org/author/38237513900
    ID: 38237513900
    Order: 1
    Author Affiliations:
    • Department of Electrical Engineering, KAIST, Daejeon, South Korea
  • Author Name: Jun-Sik Kim
    Affiliation: Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
    Author URL: https://ieeexplore.ieee.org/author/37068806700
    ID: 37068806700
    Order: 2
    Author Affiliations:
    • Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA
  • Author Name: In-So Kweon
    Affiliation: Department of Electrical Engineering, KAIST, Daejeon, South Korea
    Author URL: https://ieeexplore.ieee.org/author/37270474800
    ID: 37270474800
    Order: 3
    Author Affiliations:
    • Department of Electrical Engineering, KAIST, Daejeon, South Korea

Image Sensor

• sensor_type: CMOS
• resolution: 1600x1200
• dynamic_range: Not specified
• pixel_size: Not specified
• dark_current: Not specified

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• shutter_speed: 1/15s

Applications & Benefits

• cell_imaging: Not specified
• benefits: CMOS image sensors are used in various applications such as smartphones, medical devices, and automotive systems, enhancing imaging capabilities.

Supporting Organizations

• supported_by: Korean MOST, MIC, and Agency for Defense Development.

Manuscript Details

• publication_date: 17-22 June 2007

Relevancy Score

• score: 8
• missing_fields:
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • power_consumption
  • noise
  • applications_benefits.cell_imaging
  • optical_data

Processed JSON Filename

request_0b488f54-1eae-4676-8178-a9ac3492a709-sensor_noise_modeling_using_the_skellam_distribution_application_to_the_color_edge_detection.json