SPRACU7A December   2020  – March 2021 TDA4VM , TDA4VM-Q1

 

  1.   Trademarks
  2. 1 Introduction
  3. 2 Getting Started
    1. 2.1 Hardware Requirements
    2. 2.2 Software Requirements
    3. 2.3 Lab Requirements
  4. 3 IQ Tuning Prerequisites
    1. 3.1 Requirements for Tuning on Target
    2. 3.2 Requirements for Tuning on Simulator
  5. 4 VPAC Overview
    1. 4.1 Block Diagram
    2. 4.2 IP Overview
      1. 4.2.1 Lens Distortion Correction (LDC)
        1. 4.2.1.1 Features
      2. 4.2.2 Bilateral Noise Filter (BNF)
        1. 4.2.2.1 Features
      3. 4.2.3 Multi Scalar (MSC)
      4. 4.2.4 Vision Imaging Subsystem (VISS)
      5. 4.2.5 Subblocks
        1. 4.2.5.1 Raw Front End (RAWFE)
          1. 4.2.5.1.1 WDR Decompanding
          2. 4.2.5.1.2 WDR Merge
          3. 4.2.5.1.3 Defect Pixel Correction (DPC)
          4. 4.2.5.1.4 Lens Shading Correction (LSC)
          5. 4.2.5.1.5 Hardware 3A (H3A)
          6. 4.2.5.1.6 White Balance (WB)
        2. 4.2.5.2 NSF4 – 4th Generation Noise Filter
        3. 4.2.5.3 Global and Local Brightness Contrast Enhancement (GLBCE)
        4. 4.2.5.4 Flexible Color Processing (FCP)
  6. 5 Dataflow
  7. 6 IQ Tuning Process
    1. 6.1 Expectations of the Tool
      1. 6.1.1 User Expertise
      2. 6.1.2 Ease of Use
      3. 6.1.3 Troubleshooting
  8. 7 Imaging Software Architecture
    1. 7.1 Auto White Balance
    2. 7.2 AutoExposure
    3. 7.3 Dynamic Camera Configuration (DCC) Algorithm
  9. 8 Computing Tuning Parameters
  10. 9 Testing Tuning Parameters
    1. 9.1 On Target Platform – Compile Time Update
    2. 9.2 On Target Platform – Run Time Update From File System
  11. 10Live Tuning
    1. 10.1 Supported Features
      1. 10.1.1 RAW Capture
      2. 10.1.2 YUV Capture
      3. 10.1.3 AutoExposure Control
      4. 10.1.4 AutoWhiteBalance Control
      5. 10.1.5 Sensor Register Read/Write
      6. 10.1.6 Live DCC Update
        1. 10.1.6.1 Update Single Plugin
        2. 10.1.6.2 Update Multiple Plugins
  12. 11Revision History

7.3 Dynamic Camera Configuration (DCC) Algorithm

IQ tuning database for a given sensor consists of:

  • Plugin Params – Every tunable block (hardware or software) is modeled as a plugin. Each plugin can be tuned independently. Some examples of HW plugins are NSF4, GLBCE etc. Auto White Balance algorithm is a software plugin.
  • Photospace Params – Some plugins have only 1 set of parameters that stay constant through the lifecycle of the camera. WDR PWL is an example of such a plugin. However, there are plugins like NSF4, Color Fidelity, and so forth, which have a different set of parameters for different lighting conditions. The lighting conditions can be divided into photospaces. Each photospace can be tuned separately and the tuning parameters can be saved in the tuning database.

Tuning database can be queried at runtime to get the optimal parameters for a given combination of sensor ID, plugin and lighting condition.

DCC algorithm is responsible for parsing the database and returning the tuning parameters.