Round Trip Imaging: Difference between revisions

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==References==
==References==
{{1. Aptina Imaging Data Sheet, "MT9M114: 1/6-inch 720p High Definition (HD) System-On-A-Chip (SOC) Digital Image Sensor," http://www.datasheetlib.com/datasheet/1269108/mt9m114_aptina-imaging-corporation.html
1. Aptina Imaging Data Sheet, "MT9M114: 1/6-inch 720p High Definition (HD) System-On-A-Chip (SOC) Digital Image Sensor," http://www.datasheetlib.com/datasheet/1269108/mt9m114_aptina-imaging-corporation.html


2. e-CAM52A_5640_MOD - 5 Mega Pixel Camera Module, https://www.e-consystems.com/5MP-parallel-camera-module.asp
2. e-CAM52A_5640_MOD - 5 Mega Pixel Camera Module, https://www.e-consystems.com/5MP-parallel-camera-module.asp
}}

Revision as of 01:42, 14 December 2017

Introduction

With the prevalence of cameras on smartphones, the quality of every-day-use cameras has improved immensely. What was once available only through an expensive camera-only device is now available in your pocket. This prompted me to ask the question, how good does a camera have to be? Sure, the higher the quality the better the result, right? Well let us answer that question with an ISET experiment!

Background

The goal in this computational experiment was to identify how the quality of a camera affects the resulting (output) image of a predetermined image source. The source and output display remained constant while only the camera sensor parameters were varied. The quality of the camera in this study is defined by the camera read noise and the resolution of the camera sensor, specifically pixel height and width.The predetermined image source is an image that was captured using an iPhone 6 camera (1/3-inch sensor, 8 MP) shown below. The image contains typical text that a viewer might read. Since the readability of text is subjective, this experiment only yielded a qualitative measure of readability. It did however provide quantitative results on the readNoise and pixel resolution of real camera sensor modules.

Methods

The camera simulation was completed using standard functions in the ISET toolkit. The figure below diagrams the imaging pipeline. First an image is taken. That image is then converted into a scene. Various cameras are then created by modifying readNoise levels and pixel resolution in the camera.sensor structure. Each one of those cameras then captures an image and the output is displayed for the viewer.

Results

readNoise Effects

At first a wide range of noise levels was studied. Given that the default readNoise level in ISET is 1e-3, I searched camera module literature to pin down some of the real noise levels in operational camera modules. I was able to find two cameras with comparable signal-to-noise (SNR) and dynamic range (DR) levels. The table below contains SNR and DR data for the two cameras.<ref>Aptina</ref>


Table 1 - Camera Data
Camera SNR DR Cost ($) Resolution
Aptina 37 70.8 5.08 720p
e-con 36 68.0 19.0 1080p


Conclusions

References

1. Aptina Imaging Data Sheet, "MT9M114: 1/6-inch 720p High Definition (HD) System-On-A-Chip (SOC) Digital Image Sensor," http://www.datasheetlib.com/datasheet/1269108/mt9m114_aptina-imaging-corporation.html

2. e-CAM52A_5640_MOD - 5 Mega Pixel Camera Module, https://www.e-consystems.com/5MP-parallel-camera-module.asp