IMAGE
COMPRESSION USING ZEROTREES OF WAVELET COEFFICIENTS
Compression
Compression is a data processing method that analyzes and condenses data in files, creating a smaller file while maintaining as much quality as possible.
Large files, such as graphics or sound, are often compressed using various mathematical formulas, such as JPEG and LZW for graphics or MPEG for sound.
There are 2 Types of Compression
Lossless compression is a type of compression algorithm that reduces file size without losing any data. Typically this is done by finding and eliminating redundant information. Lossless compression never removes any information from the original file. It relies instead on representing data in mathematical formulas. GIF and PNG file formats use lossless compression.
Lossy compression reduces file size by removing "unnecessary" data. The data is eliminated based on a number of sophisticated mathematically-based formulae. Lossy compression removes image details that are (in theory, at least) too small for the human eye to notice. The JPEG format uses lossy compression.
Image
Compression using zerotrees of wavelet coefficients comes under lossy compression.
We have developed our own MATLAB code
for compressing 24 bit True Color RGB Images by various scales corresponding to
different thresholds taken.
We have tested our code on various images of different attributes and
dimensions and we have presented the outputs in terms of
‘Percentage Compression with respect to Original Image Size’
and ‘Signal to Noise Ratio (db)’.
Some Basic
terms
Pixel
A pixel is the basic unit of measurement for computers. It means "picture element." Most monitors have either 72 or 100 pixels an inch.The more pixels per inch, the higher the resolution, and the finer the display quality.
Bit Depth, Color Depth
Bit depth is the number of bits in each pixel. Color depth is the maximum number of colors in an image and is based on the bit depth of the image and of the displaying monitor. Color depth is sometimes called color resolution.
One bit produces two possible colors. If there are 2-bits per pixel, the number of colors each pixel can display rises to four and so on.
True Color
True color is an image with a color resolution of 24 bits or more, resulting in a possible 16+ million colors.
RGB Images
RGB stands for Red, Green, Blue. These are the three colors that make up all colors on a monitor. Added together at 100% of their value, they make white. The complete absence of all three makes black. Various percentages in-between make up millions of different colors.
RGB formats, also known as true-color, use 8 bits of data for each Red, Green, and Blue value. Together, this forms a 24-bit pixel palette which has 16.7 million colors (224=16,777,216 colors). JPEG images – whose bit depth can be 16, 24, or 32 – are RGB images.
The chart below shows some colors and their RGB values:
Bitmapped Images
A bitmapped image file contains a rectangular map of the image's pixels (bits) – where each pixel is located, and what color it is. GIF and JPEG, the most commonly used graphics file formats on the Web, are both bitmapped formats.
An artifact is a visual error
typically caused by inadequate sampling when reducing resolution or applying
transparency with alpha masks. Common artifacts are stray pixels in transparent
areas and jagged edges along diagonal or curved object boundaries.