Storing Images

Concepts of Storing Images

Digital images are made of tiny dots called pixels.
Each pixel holds a value representing its colour.
The resolution of an image is the total number of pixels in it – typically described in terms of the number of pixels in the horizontal and vertical dimensions.
The more pixels an image has, the higher its resolution is and the more detail it contains.

Bitmap images or raster graphics are made up of a grid of pixels where each pixel is assigned a specific location and colour value.
They are called bitmap because they contain a map of bits, a reference to the colour of each pixel.
The more pixels used in an image (density), the larger the file size – this is also known as the bit depth.
High resolution images have high bit depth and thus produce larger files sizes.
Poor scaling is a downside to bitmap images. If you zoom in too much or stretch it, the image becomes pixelated.

Vector images are made up of paths, not pixels. These paths consist of a start and end point, along with other points, curves, and angles along the way.
A path can be a line, square, triangle or a curvy shape – these paths make up objects.
Each of these objects can be edited individually, without affecting other objects in the image.
Because vector images are not resolution-dependent, they scale without losing quality or becoming pixelated.
Vector images are resolution-independent and can be scaled to any size without losing clarity or detail.
These images are ideal for logos, text, and simple illustrations that need to be scaled to different sizes.

The colour depth also known as bit depth refers to the amount of data stored for each pixel’s colour.
In a monochrome (black and white) image, each pixel is represented by one bit (0 is black, 1 is white).
An image with a colour depth of 1 bit can display 2^1 = 2 colours, i.e., black and white.
An image with a colour depth of 8 bits can display 2^8 = 256 colours.
The higher the bit depth of an image, the higher the number of tones (greys or colours) that can be displayed.

Image compression is vital for reducing the size of an image file without degrading the quality of the image beyond an acceptable level.
Lossless compression allows the original data to be perfectly reconstructed from the compressed data.
Lossy compression permits reconstruction only of an approximation of the original data, with the potential for significant degradation if the image is compressed a lot. This is commonly used for internet image and streaming video transmission.
Image compression can greatly reduce storage requirements, thus saving costs and enabling more efficient data transmission.