seminar code
09-08-2014, 02:32 PM
Image Compression Using H.264 And Deflate Algorithm
[attachment=66808]
Abstract
Compound image is combination of text,
graphics and pictures. Compression is the process
of reducing the amount of data required to
represent information. It also reduces the time
required for the data to be sent over the Internet
or Web pages. Compound image compression is
done on the basis of lossy and lossless
compression. Lossy compression is a data
encoding method that compresses data by
discarding (losing) some data in the image.
Lossless compression is used to compress the
image without any loss of data in the image. Image
compression is done using lossy compression and
lossless compression. In this paper different
techniques are used for compressing compound
images. The performance of these techniques has
been compared.
INTRODUCTION
Image processing is a multidisciplinary field
which contains elements of photography, computer
technology, electronics, and mathematics. Digital
image processing is used to improve the appearance
of an image to a human observer to extract from
image quantitative information that is not readily
apparent to a human perception [1]. Due to the
development of computer and network technologies,
compound image with mixed text, graphics and
natural picture are seen everywhere, such as captured
screen, web page, scanned electronic documents,
slides posters and so on. Compound image is a
combination of text, graphics and pictures. Figure 1
is an example for compound image. Image
compression is used to reduce irrelevance and
redundancy of the image data in order to be able to
store or transmit data in an efficient form. There are
two classifications of compression such as lossy and
lossless compressions
LITERATURE REVIEW
Wenpeng Ding, Yan Lu, Feng Wu and Shipeng
Li presented a new image compression scheme,
which is specially designed for computer generated
compound color images. First classify the image
content into two kinds: text/graphic content and
METHODOLOGY
In this paper we have taken various types of
images like normal, desktop, word, ppt and
compound images for image compression. Before
compressing these images, the image should be
segmented as 16 X 16 macroblock divisions. Then
the compression is done through lossy and lossless
methods. The processes of the above methods are
given as flow diagram in Figure 2.
Macroblock Division
In this work a segmentation based approach for
the compression of monochrome, color, and mixed
images (images which include text) is presented. [5]
The image compression is approximated by a set of
uniform regions, encoded as a set of region
boundaries (contours) and descriptions of the region
interiors. Segmentation is done as 16 X 16
macroblock divisions. After the macroblock division
the image block looks like in figure 3
Lossy Compression
The lossy compression is applied to compound
image using H.264 algorithm. Using this algorithm
images are compressed. The steps involved during
the compression are Image Transformation and
Quantization. Transformation is done through
Discrete Cosine Transform (DCT). DCT is used to
translate the image information from spatial domain
to frequency domain to be represented in a more
compact form. Quantization is used to represent the
information within the image by reducing the amount
of data. Here every image is encoded by dividing it
into blocks and assigning to each block the index of
the closest codeword. Figure 4 and 5 is an example
for transformation and quantization of image.
Lossless Compression
Lossless compression is applied to compound
image using Deflate compression algorithm. Deflate
compression is a lossless data compression algorithm
that uses a combination of the LZ77 algorithm and
Huffman coding. The LZ77 Compression Algorithm
is used to analyze input data and determine how to
reduce the size of that input data by replacing
CONCLUSION
In this paper we are compressing five different
types of images like normal, compound, word,
desktop and ppt images. All these images are
compressed using both lossy and lossless. H.264 is
used for lossy and deflate is used for lossless. So
while comparing the lossy and lossless compression
ratio and time, the lossy algorithm provides better
compression ratio and time for all types of images.
[attachment=66808]
Abstract
Compound image is combination of text,
graphics and pictures. Compression is the process
of reducing the amount of data required to
represent information. It also reduces the time
required for the data to be sent over the Internet
or Web pages. Compound image compression is
done on the basis of lossy and lossless
compression. Lossy compression is a data
encoding method that compresses data by
discarding (losing) some data in the image.
Lossless compression is used to compress the
image without any loss of data in the image. Image
compression is done using lossy compression and
lossless compression. In this paper different
techniques are used for compressing compound
images. The performance of these techniques has
been compared.
INTRODUCTION
Image processing is a multidisciplinary field
which contains elements of photography, computer
technology, electronics, and mathematics. Digital
image processing is used to improve the appearance
of an image to a human observer to extract from
image quantitative information that is not readily
apparent to a human perception [1]. Due to the
development of computer and network technologies,
compound image with mixed text, graphics and
natural picture are seen everywhere, such as captured
screen, web page, scanned electronic documents,
slides posters and so on. Compound image is a
combination of text, graphics and pictures. Figure 1
is an example for compound image. Image
compression is used to reduce irrelevance and
redundancy of the image data in order to be able to
store or transmit data in an efficient form. There are
two classifications of compression such as lossy and
lossless compressions
LITERATURE REVIEW
Wenpeng Ding, Yan Lu, Feng Wu and Shipeng
Li presented a new image compression scheme,
which is specially designed for computer generated
compound color images. First classify the image
content into two kinds: text/graphic content and
METHODOLOGY
In this paper we have taken various types of
images like normal, desktop, word, ppt and
compound images for image compression. Before
compressing these images, the image should be
segmented as 16 X 16 macroblock divisions. Then
the compression is done through lossy and lossless
methods. The processes of the above methods are
given as flow diagram in Figure 2.
Macroblock Division
In this work a segmentation based approach for
the compression of monochrome, color, and mixed
images (images which include text) is presented. [5]
The image compression is approximated by a set of
uniform regions, encoded as a set of region
boundaries (contours) and descriptions of the region
interiors. Segmentation is done as 16 X 16
macroblock divisions. After the macroblock division
the image block looks like in figure 3
Lossy Compression
The lossy compression is applied to compound
image using H.264 algorithm. Using this algorithm
images are compressed. The steps involved during
the compression are Image Transformation and
Quantization. Transformation is done through
Discrete Cosine Transform (DCT). DCT is used to
translate the image information from spatial domain
to frequency domain to be represented in a more
compact form. Quantization is used to represent the
information within the image by reducing the amount
of data. Here every image is encoded by dividing it
into blocks and assigning to each block the index of
the closest codeword. Figure 4 and 5 is an example
for transformation and quantization of image.
Lossless Compression
Lossless compression is applied to compound
image using Deflate compression algorithm. Deflate
compression is a lossless data compression algorithm
that uses a combination of the LZ77 algorithm and
Huffman coding. The LZ77 Compression Algorithm
is used to analyze input data and determine how to
reduce the size of that input data by replacing
CONCLUSION
In this paper we are compressing five different
types of images like normal, compound, word,
desktop and ppt images. All these images are
compressed using both lossy and lossless. H.264 is
used for lossy and deflate is used for lossless. So
while comparing the lossy and lossless compression
ratio and time, the lossy algorithm provides better
compression ratio and time for all types of images.