What is the difference between graphic and photographic data

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However, if you take photos in RAW format, same procedure can be done later at home using a computer. Please note that this doesn't mean that those adjustments are endless.

It is therefore better to understand the possibilities to adjust RAW images for minimum image deterioration. Therefore, the greatest benefit of the RAW data is that processing and adjustments can be performed later on the computer, otherwise would be performed at the same time when you take photographs. We also recommend using memory cards with larger capacity.

But there is no way to know whether you will be satisfied with the results of photos you are about to take. If you are satisfied with the results of JPEG photos, you don't have to adjust them; if adjustments are needed, select corresponding RAW files and process them.

Processing means compensation of the three primary colors of RAW data, including adjustments of brightness or color. This processing is performed for an entire image. Vector graphics have two downsides that can and often do cause trouble in real-world applications. First, because vector graphics are redrawn on the fly by the graphics program with which they are displayed, it can happen that there are differences in how the same graphic looks in two different programs, or on two different computers.

This problem occurs most frequently with text, for example when the required font is not available and the rendering software substitutes a different font. Font substitutions will typically allow the viewer to read the text as intended, but the resulting image rarely looks good. By contrast, bitmap images will always look the same. As a consequence, the file may be many megabytes in size, and it may take the rendering software some time to display the figure.

When I was a postdoc in the early s, I once created a pdf file that at the time took almost an hour to display in the Acrobat reader. While modern computers are much faster and rendering times of many minutes are all but unheard of these days, even a rendering time of a few seconds can be disruptive if you want to embed your figure into a larger document and your pdf reader grinds to a halt every time you display the page with that one offending figure.

Of course, on the flip side, simple figures with only a small number of elements a few data points and some text, say will often be much smaller as vector graphics than as bitmaps, and the viewing software may even render such figures faster than it would the corresponding bitmap images. Most bitmap file formats employ some form of data compression to keep file sizes manageable. There are two fundamental types of compression: lossless and lossy.

Lossless compression guarantees that the compressed image is pixel-for-pixel identical to the original image, whereas lossy compression accepts some image degradation in return for smaller file sizes. To understand when using either lossless or lossy compression is appropriate, it is helpful to have a basic understanding of how these different compression algorithms work. Imagine an image with a black background, where large areas of the image are solid black and thus many black pixels appear right next to each other.

Each black pixel can be represented by three zeroes in a row: 0 0 0, representing zero intensities in the red, green, and blue color channels of the image. The areas of black background in the image correspond to thousands of zeros in the image file. Now assume somewhere in the image are consecutive black pixels, corresponding to zeros. Instead of writing out all these zeros, we could store simply the total number of zeros we need, e.

In this way, we have conveyed the exact same information with only two numbers, the count here, and the value here, 0. Over the years, many clever tricks along these lines have been developed, and modern lossless image formats such as png can store bitmap data with impressive efficiency.

However, all lossless compression algorithms perform best when images have large areas of uniform color, and therefore Table Photographic images rarely have multiple pixels of identical color and brightness right next to each other. The camera records the signal from the image sensor without doing image processing. Illustrations shown here are intended to serve only as informative examples and have been simplified. Actual screen details will differ. The highest level of picture quality.

It is a good idea to use Fine if you are going to make large prints or manipulate or otherwise process your images on a PC. The picture quality is not as good as Fine, but, depending on the characteristics of the image, any differences may be almost imperceptible.