Search This Blog by Google

Search This Blog

Welcome to Dijemeric Visualizations

Where photography and mathematics intersect with some photography, some math, some math of photography, and an occasional tutorial.

Total Pageviews

Sunday, April 04, 2010

What is Detection? What's it Mean for Photography?

Noise, Observations, Detection
Noise in our daily observations, in analytical measurements, and in photography obscures informational content.  That information can be in a conversation, a test result on a water sample, or detail in a photograph.  Whether we can extract information from a measurement or observation depends upon the sensitivity and selectivity of the measurement method otherwise known as detection and quantitation capabilities.  In this series on detection and quantitation, post 1 will introduce the concepts, post 2 will demonstrate the use of detection and quantitation in a laboratory setting, and post 3 will develop the mathematical concepts.  Posts 4-6 will provide examples as applied to photography.

Detection and Quantitation in an Everyday Experience
Let me start with an example based on this scene from the bazaar in Cairo.  As the two women walk through the gate, the woman to the right turns and asks her friend about the wares of the merchant ahead of them.  The other woman knows her friend is talking to her but cannot hear her above the crowd so asks her to speak up.  She can now hear her friend but cannot understand her words. This is detection.  An observation or measurement distinguishable from the noise is a detection.  She asks her to speak up some more and finally can hear her words and understands her question.  This is quantification; an observation or measurement sufficiently different from the noise to allow decisions to be made.

In the next two blogs I will discuss more of the theoretical concepts before presenting some applications to photography.  I hope to show how the concepts of detection and quantitation relate to photography and are the theoretical basis for dealing with digital noise, optimization of shadow details, and building models to distinguish unaltered vs modified digital images.

The Promise for Photography
Here's the proposal: a photograph with maximum DOF (i.e., minimum aperture), great shadow detail, shot in low light, at low ISO, and exposed for the low end of the highlights (zone 8).  Using the theories on digital noise and detection, I will show you how it can be done.

Detection in the Testing Laboratory for a discussion of detection and quantitation concepts in the testing laboratory and how laboratories can check to ensure that the test results are valid.

For those curious about the photo. It is a composite of five photographs all taken within a one hour period in the Cairo souk (market place). Western elements in the main image were replaced with more traditional subjects: two men in jeans walking under the arch were replaced with the two women; the apartments in the background were replaced with a scene from a nearby street; the women talking to the merchant were from a nearby street talking to another merchant and replaced a group of tourists. The turbaned merchant and man entering from the right are as they appeared in the primary photo.

1 comment:

damead said...

Hi, Ken,

This page actually does not answer the question in the title. You give the fundamental definitions of detection and quantification, but you go from there to describing the components of the image, a totally unrelated point. Then you promise to answer the question in a later blog. Clicking to the next page just puts the visitor in the laboratory with no mention of photography except the back-link title. You should make a brief but clear connection so the reader knows where you are going and keeps an eye out for the promised perusal.