Use HDR Techniques To Get The Best Image Detail

Download your free copy now!

 

Use high dynamic range techniques to capture detail in highlights and shadows even in scenes with extreme contrast.

 

1. Why Everybody Needs HDR … Sometimes | Coming Soon

2.  What In The World Is HDR ?

3.  What Is Exposure Value ?

4.  Using Histograms – ETTR

5.  Why Your Camera’s Auto HDR Feature Is Inferior 

6.  How To Set Your Camera To Auto Bracketing 

7.  How Many Exposures Do You Need For HDR Merges ? 

8.  Making HDR Merges Is A Four Step Process

9.  5 Photoshop Tools To Make The Most of Shadows & Highlights Without HDR

10.  3 Ways HDR Software Can Benefit Single Exposures | Coming Soon

11.  Using HDR Software To Sharpen Photographs

12.  HDR With One Exposure

13.  HDR With Two Exposures

14.  HDR with Lightroom | Coming Soon

15.  HDR With Photoshop | Coming Soon

16.  HDR With Photomatix | Coming Soon

17.  HDR With NIK’s HDR Efex Pro | Coming Soon

18.  HDR With Aurora HDR | Coming Soon

19.  HDR Panoramas | Coming Soon

20.  Refine HDR With Photoshop Layer Blending | Coming Soon

21.  7 HDR Artifacts & How To Avoid Or Cure Them 

22. 8 HDR Myths Debunked 

23. Quick Answers To The 5 Most Asked HDR Questions 

 

Sign up for Insights for news of new content!

What In The World Is HDR ?

evcrcomparisons

hdrevs_425

1 EV is equivalent to 1 F-Stop of brightness

hdr_crrough

These Contrast Ration (CR) figures are approximate

Dynamic Range
Today, many people think HDR refers to the practice of merging bracketed exposures with software, but HDR actually applies to everything in an imaging workflow - capture, processing, display, and printing.
What is HDR? HDR is an acronym that stands for High Dynamic Range. It’s the opposite of LDR or Low Dynamic Range Imaging.
What is dynamic range? In imaging, dynamic range (DR) is the highest overall level of contrast found in an image. In other fields, such as in the audio industry, dynamic range is used to describe similar phenomena. In audio, DR is defined as the logarithmic ratio between the largest readable signal and background noise. DR is akin to signal-to-noise ratio. In imaging, DR refers to the entire image. Consider an image a signal – and every signal has some noise.
The values used to specify dynamic range can be charted on multiple scales. Whatever language is used to describe this phenomenon, two critical factors must be addressed; the total range of brightness and the fineness of the steps used within the scale.
Two scales are most useful for images – exposure value and contrast ratio. Exposure value (EV) is easier to use while contrast ratios better display logarithmic increases in light intensities. Both refer to the same phenomenon – relative increase or decrease in brightness.
The EV scale makes it easy to compare the ratios rather than the big numbers of logarithmic progressions; each successive EV rating represents a doubling of values. The exposure value (EV) scale has been used by photographers for ages. The International Organization for Standards (ISO) defines EV 0 at an aperture size of 1 and a 1 second exposure time. The same EV can be achieved with any other combination of fstop and shutter speed that produces the same amount of light.
‘The contrast ratio scale specifically delineates values; when you use this rating you instantly see how much greater each step in a progression is than the previous one because the numbers are so much bigger. You can convert EV to contrast ration or vice versa with the right formulas. 2 (power of EV) = contrast ratio (2*8=256 for a contrast ratio of 256:1) or EV=log10(contrast ratio)*3.32 (log10(4000)*3.32=12EV
Dynamic range, gamut, and bit-depth are often confused. Though related, they’re all different. Dynamic range refers to a total range of luminosity values. Gamut refers to a total color capacity, including saturation. Bit depth refers to the number of points of data between values or the fineness of the increments in the scale. Just because an image is wide gamut doesn’t mean it is HDR or has high bit depth, but it will contain more and potentially better data if it does. Just because an image is HDR doesn’t mean it is wide gamut and has high bit depth, but it will contain more and potentially better data if it does. You can’t convert low dynamic range, small gamut, low bit depth information to high bit depth, wide gamut, high dynamic range information. To get it and use it, you have to capture high quality information upon exposure and preserve it throughout your workflow.


Insights Members can login to read the full article.
Email: