By now, most people have heard the news of the hunter who captured the image of a young male mountain lion in Trego County.

When I first heard the news, I had asked to get my hands on the original image so I could verify its integrity.

It was well after the news broke when I was able to get the digital photographic file. I had many questions about the picture. Was it legitimate?

The Kansas Department of Wildlife and Parks examined the image and went to the site where the photograph was said to be taken. They verified the location, wading through a huge pile of corn, and made some scientific measurements to determine if the size of the animal was relative to an actual mountain lion. Based on photographic evidence which shows the length of the tail, they concluded it was a picture of a mountain lion in Kansas.

However, I am not sure they were really able to verify one element. Could the picture have been manipulated?

There are a number of photo programs that are capable of changing elements within a digital file.

Photographic trickery runs rampant, and diagnosing photographic manipulation is difficult to determine because the changes occur at the pixel level. While there is mastery in photographic trickery, it is detectable to the trained eye.

Image analysis to determine a fake first begins by examining the digital data that resides in each file. Digital cameras render pixel data and other digital documenting data that stays with the file.

Most photographic programs can uncover this information by logging creation dates, and subsequent dates when the image is changed from its original form.

An examination of the pixels that make up the image is next. Each pixel is a square particle and there may be millions that make up a digital picture. Fakes can be determined with a trained eye by examining each pixel, its value and its relationship to adjacent pixels.

This can take hours of study to make a judgement.

And that is all it can be is a judgment based on neighboring pixels. Pixel replacement within a digital photograph is hard to track. However, there are algorithms that can highlight areas of concern within a digital file. The best one out there was written by a leading computer scientist, Hany Farid, who runs the Image Science Group at Dartmouth College in Hanover, N.H.. The algorithm is a form of digital forensics, using computational and mathematical techniques to detect tampering in digital images.

But one doesn't always have to go that far to investigate an image.

For example: I was able to uncover a variety of information about the mountain lion photographs in question using Photoshop. I use it every day in my line of work.

1) The photograph was taken with a Fujifilm Finepix S5700 S700 7.1 mega-pixel digital camera. The camera resolution could have been set on low, as the file I received is not the 7.1 mega-pixel full resolution file that the camera is capable of producing.

2) The image was taken with the following camera settings. The camera was set with an ISO or ASA rating of 400. The lens' focal length was 6.3 mm. The shutter speed was 1/45 second. The lens aperture value was f3.5.

3) The camera's time and date stamp was likely not set as the camera recorded the following information. Date/Time 2010-05-30T06:01:36-5:00. If the camera was set properly when purchased with time and date, the stamp would indicate the image was taken on May 30, 2010 at one hour, one minute and 36 seconds after midnight Central Standard Time. Of course, as you know, it is still just October 2009,

4) Other data residing with the file indicates the flash did not fire, the camera was set at Auto Mode (3), not to mention a few more bits of useless information.

After examining the image pixel by pixel, I see no evidence of tampering. The camera's time and date stamp offers no clues to verify the image. In my mind, there is still room for skepticism because the image quality is so poor.

I know the difficulty of photographing wildlife -- it is one of the things I do.

Skeptics look for picture proof for verification.