This document discusses an upcoming technology called compressive sensing that allows photographers to directly take compressed pictures without having to later compress raw files on a PC. Compressive sensing uses fewer "measurements" during image capture, which can result in benefits like less space needed for photos, lower MRI scan times, and longer battery life for devices by reducing power needs. One startup company applying this technology is InView Corp. Python libraries exist for working with compressive sensing algorithms.

1. An upcoming technology
- Ashok
Govindarajan
26-12-2016 Technology sharing series 1

2. Contents
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• Upcoming technology
• What is the problem definition?
• Solution, benefits, startups trying to solve this problem, links to Python

3. Problem statement – Block diagram level
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What does a photographer
do? Take photographs which
are stored in the camera.
(RAW format) – Example size,
say 1MB
Processes them in the PC
for compression;
RAW file to JPEG
conversion; Uploads
them. (JPEG Format) –
Compressed size is 50 kB;
Compression factor = 20
Can he/she photograph, such that, we get a 50kB image directly
without the the 1MB to 50 kB processing?
That is, can the photographer directly take pictures that are compressed?

4. Problem statement – flow-wise and a few questions
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Is it possible to avoid step 2? If yes, is there a technology?
What are the advantages/benefits? Under what context are the advantages/benefits
most needed?

5. Solution, Benefits, Startup company and Links to Python
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• Solution Space : Compressive Sensing
• Benefits : Lesser space for photos taken by digital cameras and lower MRI time.
Primarily needed in sensor networks where lesser “measurements” mean lesser
power, so LONGER BATTERY LIFE
• Startup Company : http://inviewcorp.com/applications/compressive-
sensing/#.WFktx1N97IU ; Latest updates in June 2016.
• Links to Python : https://pypi.python.org/pypi/pycompsense
 pycompsense is a toolbox for compressed sensing and sparse reconstruction
algorithms.
• Info : Provided a simplified explanation, to ease understanding in the community

6. 26-12-2016 Technology sharing series 6
Thank You