10 Most Magnificent Trees in the World. "A tree is a wonderful living organism which gives shelter, food, warmth and protection to all living things.
It even gives shade to those who wield an axe to cut it down" - Buddha. There are probably hundreds of majestic and magnificent trees in the world - of these, some are particularly special: 10. Lone Cypress in Monterey (Image credit: bdinphoenix [flickr]) (Image credit: mikemac29 [flickr]) Buffeted by the cold Pacific Ocean wind, the scraggly Lone Cypress [wiki] (Cupressus macrocarpa) in Pebble Beach, Monterey Peninsula, California, isn't a particularly large tree. 9. As a hobby, bean farmer Axel Erlandson [wiki] shaped trees - he pruned, bent, and grafted trees into fantastic shapes and called them "Circus Trees.
" Basket Tree (Image credit: jpeepz [flickr]) The two-legged tree (Image credit: Vladi22, Wikipedia) Ladder tree (Image credit: Arborsmith) Axel Erlandson underneath one of his arborsculpture (Image credit: Wilma Erlandson, Cabinet Magazine) 8. 7. Chandelier Tree. 6. 5. 4. 3. Color matching functions. Sensor sharpening. Sensor Sharpening The idea that narrow band sensors result in illumination independent ratios of adjacent pixel channel values led Computational Vision Lab researchers [FINLAY94a] to consider the general conditions that lead to stable ratios.
Consider two adjacent image pixels A and B. The ratio of responses for the kth sensor type at the two locations is where and represent the surface reflectance at the scene points corresponding to pixels A and B. Will be identical or nearly so. On the top and bottom, obviously we cannot legitimately do so in general since appears within the integral. However, could be cancelled out is if the sensor sensitivity function were extremely narrowband (i.e., the Dirac delta) so that its response was only non-zero at a single wavelength, . In which case the illuminant’s effect can be cancelled out and eliminated. For example, if the sensor response in kth band under illuminant A is and the response under illuminant B is and their ratio is then k=1...3 (3)
Cognitive Daily: Artists look different. These two pictures represent the eye motions of two viewers as they scan a work of art with the goal of remembering it later.
One of them is a trained artist, and the other is a trained psychologist. Can you tell which is which? How about for this picture? Art teachers have noted that when beginning students attempt to draw accurate portraits, they tend to exaggerate the size of key features: eyes and mouths are too big relative to the size of the head. Trained artists learn to ignore these temptations and draw the world as it really appears. Stine Vogt and Svein Magnussen showed 16 pictures including these two to trained artists and non-artists (psychologists) enrolled in Norway’s top graduate programs in their respective disciplines, using eye-tracking cameras and software to monitor where they looked.
Vogt and Magnussen defined key areas of each picture — small regions around focal objects such as human bodies or faces. So who was better at remembering pictures? Human Vision and Digital Imaging. A profitable look under the hood leading to Lab color On this page— Under construction...
Last updated October 22, 2009 Why Look Under the Hood? This article is dedicated to the proposition that the workings of human vision should inform the workings of digital photography. Such understandings are by no means substitutes for photographic imagination and judgement, but they can inform the exercise of those faculties. Nagging Questions Throughout my research for the dpFWIW article B&W digital, two questions kept popping up: Why are these colorless (B&W) images so satisfying? Then, late in the game, I happened upon one of Monet's many "Water Lilies" panels on local display. That moment in the museum launched the research for this article, but I now realize that its ultimate inspiration was a book I'd read 2 years earlier—Robert Jourdain's Music, the Brain and Ecstasy relating human brain-ear machinery to what goes on in music.
Perceptual Image Difference Utility.