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HDR : myths and misinterpretations

   I've become aware of widespread  disinformation on HDR. Reviewers of video products and software make claims based on an incomplete and faulty understanding of HDR.    HDR does this, HDR does that, HDR will do this and that.    Many such people do not understand the difference between an HDR image and the compressor that makes the image viewable and printable. The HDR is the attempted storage of  an aspect of 'reality'. This 'reality' is too much for computer displays and printers so someone writes compression software to make the HDR acceptable, i.e., viewable on monitors and printable on printers. There are an infinite number of ways to do this. The HDR image you see and like so much may have been compressed by a different method than the same HDR another person may see, resulting in two visually different images.    This boils down to a matter of interpretation. Much of what is being attributed to HDR images is really the effect of different compressors,

HDR history

   As a precursor, let me reiterate, these blogs are for intelligent people with a university background and courses in mathematics, engineering, physics and other of the hard sciences.    The first HDR image was the result of the independent work of Prof. Paul Debevec, U.C., and Gregory Ward Larson, JPL.    Prof. Debevec developed an algorithm to composite several images into one. His work was published in a research paper still available online. In the back of the paper is a Matlab script of the algorithm. Matlab is published by Mathworks, Inc, and is the foremost mathematics laboratory,  Matlab is widely used by scientists and professionals in a science related field.    One of the unknown benefits in HDR is the ability two construct an HDR image with only two exposures (images) if the same film is used for several images. Prof. Debevec derived an additional algorithm for determining the film character and using that data to reduce the number of images needed for a HDRI (High Dy

High Dynamic Range imaging

   High Dynamic Range imaging (HDR) has come some way since I first ran across the initial phenomenon in the late 90's. HDR is a file format for images that contains numbers. The numbers represent so much pictorial information, no monitor or printer can display the data in it's entirety. The HDR image is like a digital negative in as much as making a print involves adjusting the enlarger aperture and light source to an exposure level consistent with the photographer's goals. No one exposure represents the negative entirely. Lighter exposures reveal different details than a lower exposure.    An HDR image is formed by taking a series of images that vary only in shutter speed, and combining them in a defined way. Think of an unsliced loaf of bread as an image. T he several images represent every nth slice in a sliced loaf. The other slices are filled in using highly educated guesses to get a full, sliced loaf. Each slice represents a specific shutter speed.    Better versi

Film Scanning

   I for got to mention in my introduction to this blog, that film scanning would also be discussed. I inherited a large number of photo negatives from my father. These negatives range in dates from the late 1930's to the 1970's.    Fortunately, most of the film is in 620 format. This large format preserves more detail than smaller formats such as 35mm. The film subjects are of several types. Family photos before and after my father married my mother and photos from his time in the military, Army Air Corp.    I decided many, years ago, to attempt to digitize the images and store them on my computer. There was little technology and knowledge available on the topic then. Much more has developed, but what I discovered, remains to this day, as far as I know, the most advance process available. Unfortunately, I won't be able to share the details since my copyrights and patent rights are not protected. I will reveal much useful information though.
This blog is dedicated to imaging. The initial primary focus will be high dynamic range imaging. The application of mathematics to imaging will be included. Color management in general, and specifically, on a Windows PC is also part of the discussion.