March 2nd, 2011 
Andrei All the pixels in a photo have certain level of brightness ranging from black to white. These values of the pixels serve as the input for the computer monitor. Due to technical limitations, CRT monitors output these values in a nonlinear way:
Output = Input ^ Gamma
Gamma
February 28th, 2011 Andrei The dynamic range of any sensor used in digital cameras is defined by the largest possible signal divided by the smallest possible signal it can generate. The largest signal represents the maximum amount of light that can be converted by the sensor into a unique digital value that represents a pixel into a photo. The smallest signal represents the value generated by the sensor when it doesn’t receive any amount of light. It is also known as the “noise floor”. Cameras with a large dynamic range are able to capture shadow detail and highlight detail at the same time. Even the most advanced sensors today cannot compete with human eye in terms of dynamic range.
Dynamic Range
February 4th, 2011 Andrei There are two ways in which digital images can be compressed: lossless and lossy.
Lossless Compression
Lossless compression is similar to what WinZip does. For example, if you compress a document into a ZIP file and later extract and open the document, the content will be identical to the original. No information is lost in the process. Only some processing time was required to compress and decompress the document. TIFF is an image format that can be compressed in a lossless way.
Lossy Compression
Lossy compression reduces the image size by discarding information and is similar to summarizing a document. For instance, you can summarize a 100 page document into a 75 page or 20 page document that represents the original, but you cannot create the original out of the summary as information was discarded during summarization. JPEG is an image format that is based on lossy compression.
February 1st, 2011 Andrei A color space (or color model) is an abstract mathematical model describing the way colours can be represented as groups of numbers, typically as three or four values or color components (e.g. RGB and CMYK are color models).
The Additive RGB Colors
The cells inside our eyes (called cone-shaped cells) are sensitive to red, green, and blue. We perceive all other colors as combinations of these three primary ones. Computer monitors emit a mix of red, green, and blue light to generate various colors. For example, combining the red and green “additive primaries” will generate yellow. Combining all additive primaries (red, green and blue) will generate white.
Additive RGB Colors
January 24th, 2011 Andrei In digital computers world bits are the smallest pieces of information that can be stored. One bit of information has a value of either “0″ or “1″. This values correspond with the two states of a switch: “on” and “off”. The electronic switches used in computers are called transistors.
Bits
January 10th, 2011 Andrei In this second (and last) part we will talk about Moire, Maze Artifacts, Noise and Sharpening Halos.
Moire and Maze Artifacts
If a scene contains areas with repetitive detail which exceeds the resolution of the camera, a wavy moire pattern can appear. Anti-alias filters reduce or eliminate moire but also reduce image sharpness. Sometimes, moire can cause the camera’s internal image processing to generate maze artifacts. Here you can see an example of moire and maze artifacts:
Moire and Maze
January 8th, 2011 Andrei As holidays past, I think you will find these websites very useful:
January 5th, 2011 Andrei In digital photography artifacts refer to the undesirable modifications caused by the sensor, optics, and internal image processing algorithms of the camera. On low budget compact cameras these artifacts are more visible and easy to identify. On the other hand, top DSLR cameras will require a more careful analysis to identify these artifacts and most of the times they don’t represent a disturbing issue. In this first part we will talk about Blooming, Chromatic Aberrations, Jaggies and JPEG Compression.
Blooming
Every pixel in a digital image is the corespondent value of an electrical charge. This in turn is directly related to the number of photons that will fall on the pixel’s photodiode in time of exposure time. If the exposure time is to long, the electrical charge will reach it’s maximum and will overexpose the corresponding pixel. Blooming occurs when this extra electrical charge affects also the surrounding pixels, causing a loss of details in the photo. Here is an example:
Blooming
January 2nd, 2011 Andrei All the pixels in a digital image have a square form. For this reason if you zoom in on areas where there are diagonal lines or circles, you will observe that they have a jagged appearance. This is the aliasing or steps effect. Here you can see an example:
Aliasing
December 14th, 2010 Andrei In this final night photography lesson we will talk about one of the most spectacular man made light effects: fireworks. Capturing some exciting fireworks images needs careful planning and, why not, a bit of luck. As fireworks are usually set off at night, this does give the chance to use long exposures without fear of over exposure unless there is a large amount of ambient artificial lighting showing in the image or traces of daylight. The long exposure is necessary if you want to capture the whole pattern of a burst which takes about 5 seconds to complete. Most of the times you will want to capture at least 2 bursts in one shot for a much impressive photo, so the exposure will have to be longer.
Night Photography - Fireworks
