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OrderArtwork.com Turns Photo Into Customized Oil Paintings

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You know that there is no magic solution; the best optimization is to start with the highest quality image possible. Ensuring this means using proper technique, a high resolution camera, a low noise setting and a good RAW file converter. Once all of this has been attempted, optimizing digital photo enlargement can help you make the most of your image.

DIGITAL IMAGE INTERPOLATION

Image interpolation occurs in all digital photos at some stage-- whether this be in bayer demosaicing or in photo enlargement. It occurs anytime you resize or remap (distort) your image from one pixel grid to another. Image resizing is necessary when you need to increase or decrease the total number of pixels, whereas remapping can occur under a wider variety of scenarios: correcting for lens distortion, changing perspective, and rotating an image.

Even if the same image resize or remap is performed, the results can vary significantly depending on the interpolation algorithm. It is only an approximation, therefore an image will always lose some quality each time interpolation is performed. Artist Experts from OrderArtwork.com have a good understanding of how the results may vary-- helping you to minimize any interpolation-induced losses in image quality.

Common interpolation algorithms can be grouped into two categories: adaptive and non-adaptive. Adaptive methods change depending on what they are interpolating (sharp edges vs. smooth texture), whereas non-adaptive methods treat all pixels equally.

Non-adaptive algorithms include: nearest neighbor, bilinear, bicubic, spline, sinc, lanczos and others. Depending on their complexity, these use anywhere from 0 to 256 (or more) adjacent pixels when interpolating. The more adjacent pixels they include, the more accurate they can become, but this comes at the expense of much longer processing time. These algorithms can be used to both distort and resize a photo.

Adaptive algorithms include many proprietary algorithms in licensed software such as: Qimage, PhotoZoom Pro, Genuine Fractals and others. Many of these apply a different version of their algorithm (on a pixel-by-pixel basis) when they detect the presence of an edge-- aiming to minimize unsightly interpolation artifacts in regions where they are most apparent. These algorithms are primarily designed to maximize artifact-free detail in enlarged photos, so some cannot be used to distort or rotate an image.

All non-adaptive interpolation algorithms always face a trade-off between three artifacts: aliasing, blurring and edge halos.

Adaptive (edge-detecting) algorithms do not treat all pixels equally, but instead adapt depending on nearby image content. This flexibility gives much sharper images with fewer artifacts (than would be possible with a non-adaptive method). Unfortunately, these often require more processing time and are usually more expensive.Even the most basic non-adaptive methods do quite well at preserving smooth tonal gradations, but they all begin to show their limitations when they try to interpolate near a sharp edge.

Genuine Fractals is perhaps the most common iterative (or fractal) enlargement software. It tries to encode a photo similar to a vector graphics file-- allowing for near lossless resizing ability (at least in theory). Interestingly, its original aim was not for enlargement at all, but was instead intended for efficient image compression. Times have changed since storage space is now more plentiful and fortunately, so has its application.

Shortcut PhotoZoom Pro (formerly S-Spline Pro) is another common enlargement program. It takes into account many surrounding pixels when interpolating each pixel, and attempts to re-create a smooth edge that passes through all known pixels. It uses a spline algorithm to re-create these edges, which is similarly used by car manufacturers when they design a new smooth-flowing body for their cars. PhotoZoom has several settings-- each geared towards a different type of image.

Note how PhotoZoom produces superior results in the computer graphic above, as it is able to create a sharp and smooth-flowing edge for all the curves in the flag. Genuine fractals adds small-scale texture which was not present in the original, and its results for this example are arguably not much better than those of bicubic. It is also worth noting though that Genuine Fractals does the best job at preserving the tip of the flag, whereas PhotoZoom sometimes breaks it up into pieces. The only interpolator which maintains both smooth sharp edges and the flag's tip is SmartEdge.

The above comparisons demonstrate enlargement of theoretical examples, however real-world images are seldom this simple. These also have to deal with color patterns, image noise, fine textures lighting, clarity and edges that are not easily done. It had better let professional artist to handle for you since it needs professional knowledge to do good job and is real professional job such as pimping a photo below up to a 30" X 20" family photo that is studio quality from paper to lighting and clarity and possibly a canvas or art paper type material to be printed on, which is real order from our custome from Renne Safford, AZ, who like what we did for her very much.

BASICS OF DIGITAL CAMERA PIXELS

The continuous advance of digital camera technology can be quite confusing because new terms are constantly being introduced. This tutorial aims to clear up some of this digital pixel confusion-- particularly for those who are either considering or have just purchased their first digital camera. Concepts such as sensor size, megapixels, dithering and print size are discussed.

Every digital image consists of a fundamental small-scale descriptor: THE PIXEL, invented by combining the words "PICture ELement." Just as how pointillist artwork uses a series of paint blotches, millions of pixels can also combine to create a detailed and seemingly continuous image.

Each pixel contains a series of numbers which describe its color or intensity. The precision to which a pixel can specify color is called its bit or color depth. The more pixels your image contains, the more detail it has the ability to describe.

PRINT SIZE: PIXELS PER INCH vs. DOTS PER INCH

Since a pixel is just a logical unit of information, it is useless for describing real-world prints-- unless you also specify their size. The terms pixels per inch (PPI) and dots per inch (DPI) were both introduced to relate this theoretical pixel unit to real-world visual resolution. These terms are often inaccurately interchanged (particularly with inkjet printers)-- misleading the user about a device's maximum print resolution.

"Pixels per inch" is the more straightforward of the two terms. It describes just that: how many pixels an image contains per inch of distance in the horizontal and vertical directions. "Dots per inch" may seem deceptively simple at first. The complication arises because a device may require multiple dots in order to create a single pixel; therefore a given number of dots per inch does not always lead to the same resolution. Using multiple dots to create each pixel is a process called "dithering."

A device with a limited number of ink colors can play a trick on the eye by arranging these into small patterns-- thereby creating the perception of a different color if each "sub-pixel" is small enough. A Photograph can use 128 pixel colors, however the dithered version creates a nearly identical looking blend of colors (when viewed in its original size) using only 24 colors. There is one critical difference: each color dot in the dithered image has to be much smaller than the individual pixel. As a result, images almost always require more DPI than PPI in order to achieve the same level of detail. PPI is also far more universal because it does not require knowledge of the device to understand how detailed the print will be.

The standard for prints done in a photo lab is about 300 PPI, however inkjet printers require several times this number of DPI (depending on the number of ink colors) for photographic quality. It also depends on the application; magazine and newspaper prints can get away with much less than 300 PPI. The more you try to enlarge a given image, the lower its PPI will become (assuming the same number of pixels).

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