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How can I use JPEG Compression algorithm for 1D data (e.g. a line)?
How can I create an executable JAR with dependencies using Maven?How can I convert a stack trace to a string?quantization of dct image for steganographyJPEG Compression Implementation QuestionsCUDA DCT works only when blockDim.x is 1Steganography using the DCTJPEG compression implementation in MATLABSteganography resistant to JPEG compression and manipulationLSB-DCT based Image steganographyHow are quantized DCT coeffiecients serialised in JPEG?
I have a (time series) data that looks like 21,21,22,23,24,23,.... and I'm trying to implement the jpeg algorithm in JAVA to see how the jpeg compression works on such 1D data (my plan is to compare all sorts of compression algorithms).
I know that using JPEG on text data (or in general lossy compression in text data) doesn't make much sense but my goal is to see what kind of intermediate patterns are generated (e.g. "automobile" becomes "qwses")and how much of that intermediate pattern resembles the original words over increasing compression rate. So the idea is something like this: https://www.youtube.com/watch?v=meovx9OqWJc&t=1s
My input file, as I said above, is a 1x458 matrix and contains numbers between 10 and 300; e.g. 10, 13, 14, 14, 15, 12, ...., 247,247,249,.., 284, 283
My main problem is that I am not quite sure how I should theoretically convert the JPEG algorithm (8x8 image multiplied with 8x8 DCT coefficient matrix etc is adapted for a 1xN data (a line) and what part of the implementation should I change in JPEG (e.g. how should I have dct coefficients for such data, etc.)? If someone can explain it with a pseudo code, that would also be really nice.
java compression jpeg dct lossy-compression
edited Mar 21 at 16:28
static_cast
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
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Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
I have a (time series) data that looks like 21,21,22,23,24,23,.... and I'm trying to implement the jpeg algorithm in JAVA to see how the jpeg compression works on such 1D data (my plan is to compare all sorts of compression algorithms).
I know that using JPEG on text data (or in general lossy compression in text data) doesn't make much sense but my goal is to see what kind of intermediate patterns are generated (e.g. "automobile" becomes "qwses")and how much of that intermediate pattern resembles the original words over increasing compression rate. So the idea is something like this: https://www.youtube.com/watch?v=meovx9OqWJc&t=1s
My input file, as I said above, is a 1x458 matrix and contains numbers between 10 and 300; e.g. 10, 13, 14, 14, 15, 12, ...., 247,247,249,.., 284, 283
My main problem is that I am not quite sure how I should theoretically convert the JPEG algorithm (8x8 image multiplied with 8x8 DCT coefficient matrix etc is adapted for a 1xN data (a line) and what part of the implementation should I change in JPEG (e.g. how should I have dct coefficients for such data, etc.)? If someone can explain it with a pseudo code, that would also be really nice.
java compression jpeg dct lossy-compression
edited Mar 21 at 16:28
static_cast
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55
add a comment |
I have a (time series) data that looks like 21,21,22,23,24,23,.... and I'm trying to implement the jpeg algorithm in JAVA to see how the jpeg compression works on such 1D data (my plan is to compare all sorts of compression algorithms).
I know that using JPEG on text data (or in general lossy compression in text data) doesn't make much sense but my goal is to see what kind of intermediate patterns are generated (e.g. "automobile" becomes "qwses")and how much of that intermediate pattern resembles the original words over increasing compression rate. So the idea is something like this: https://www.youtube.com/watch?v=meovx9OqWJc&t=1s
My input file, as I said above, is a 1x458 matrix and contains numbers between 10 and 300; e.g. 10, 13, 14, 14, 15, 12, ...., 247,247,249,.., 284, 283
My main problem is that I am not quite sure how I should theoretically convert the JPEG algorithm (8x8 image multiplied with 8x8 DCT coefficient matrix etc is adapted for a 1xN data (a line) and what part of the implementation should I change in JPEG (e.g. how should I have dct coefficients for such data, etc.)? If someone can explain it with a pseudo code, that would also be really nice.
java compression jpeg dct lossy-compression
edited Mar 21 at 16:28
static_cast
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
I have a (time series) data that looks like 21,21,22,23,24,23,.... and I'm trying to implement the jpeg algorithm in JAVA to see how the jpeg compression works on such 1D data (my plan is to compare all sorts of compression algorithms).
I know that using JPEG on text data (or in general lossy compression in text data) doesn't make much sense but my goal is to see what kind of intermediate patterns are generated (e.g. "automobile" becomes "qwses")and how much of that intermediate pattern resembles the original words over increasing compression rate. So the idea is something like this: https://www.youtube.com/watch?v=meovx9OqWJc&t=1s
My input file, as I said above, is a 1x458 matrix and contains numbers between 10 and 300; e.g. 10, 13, 14, 14, 15, 12, ...., 247,247,249,.., 284, 283
My main problem is that I am not quite sure how I should theoretically convert the JPEG algorithm (8x8 image multiplied with 8x8 DCT coefficient matrix etc is adapted for a 1xN data (a line) and what part of the implementation should I change in JPEG (e.g. how should I have dct coefficients for such data, etc.)? If someone can explain it with a pseudo code, that would also be really nice.
java compression jpeg dct lossy-compression
java compression jpeg dct lossy-compression
edited Mar 21 at 16:28
static_cast
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Mar 21 at 16:28
static_cast
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Mar 21 at 16:28
static_cast
1,07211521
edited Mar 21 at 16:28
static_cast
1,07211521
edited Mar 21 at 16:28
static_cast
1,07211521
1,07211521
asked Mar 21 at 14:41
ChucksterChuckster
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 21 at 14:41
ChucksterChuckster
12
asked Mar 21 at 14:41
ChucksterChuckster
12
12
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Chuckster is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55
add a comment |
So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55
So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55
add a comment |
1 Answer
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You'd need to provide more information about the nature of your 1D data, and why you think it is compressible. What patterns are you expecting to see?
For example, if it really looks like the sequence you show (21,21,22,23,24,23), then a simple model using the difference of successive values would result in data that is highly compressible by a standard lossless compressors like gzip. E.g. (21,0,1,1,1,-1).
To take advantage of higher-order correlations, what you might be looking for is an FFT. You can do an FFT efficiently on any sequence of 2n samples (not only eight samples, as the JPEG DCT does). There are libraries out there that do lossless integer FFTs, as well as other transforms like wavelets, that you can try.
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
add a comment |
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You'd need to provide more information about the nature of your 1D data, and why you think it is compressible. What patterns are you expecting to see?
For example, if it really looks like the sequence you show (21,21,22,23,24,23), then a simple model using the difference of successive values would result in data that is highly compressible by a standard lossless compressors like gzip. E.g. (21,0,1,1,1,-1).
To take advantage of higher-order correlations, what you might be looking for is an FFT. You can do an FFT efficiently on any sequence of 2n samples (not only eight samples, as the JPEG DCT does). There are libraries out there that do lossless integer FFTs, as well as other transforms like wavelets, that you can try.
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
add a comment |
You'd need to provide more information about the nature of your 1D data, and why you think it is compressible. What patterns are you expecting to see?
For example, if it really looks like the sequence you show (21,21,22,23,24,23), then a simple model using the difference of successive values would result in data that is highly compressible by a standard lossless compressors like gzip. E.g. (21,0,1,1,1,-1).
To take advantage of higher-order correlations, what you might be looking for is an FFT. You can do an FFT efficiently on any sequence of 2n samples (not only eight samples, as the JPEG DCT does). There are libraries out there that do lossless integer FFTs, as well as other transforms like wavelets, that you can try.
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
add a comment |
You'd need to provide more information about the nature of your 1D data, and why you think it is compressible. What patterns are you expecting to see?
For example, if it really looks like the sequence you show (21,21,22,23,24,23), then a simple model using the difference of successive values would result in data that is highly compressible by a standard lossless compressors like gzip. E.g. (21,0,1,1,1,-1).
To take advantage of higher-order correlations, what you might be looking for is an FFT. You can do an FFT efficiently on any sequence of 2n samples (not only eight samples, as the JPEG DCT does). There are libraries out there that do lossless integer FFTs, as well as other transforms like wavelets, that you can try.
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
You'd need to provide more information about the nature of your 1D data, and why you think it is compressible. What patterns are you expecting to see?
For example, if it really looks like the sequence you show (21,21,22,23,24,23), then a simple model using the difference of successive values would result in data that is highly compressible by a standard lossless compressors like gzip. E.g. (21,0,1,1,1,-1).
To take advantage of higher-order correlations, what you might be looking for is an FFT. You can do an FFT efficiently on any sequence of 2n samples (not only eight samples, as the JPEG DCT does). There are libraries out there that do lossless integer FFTs, as well as other transforms like wavelets, that you can try.
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
answered Mar 21 at 23:49
Mark AdlerMark Adler
59.5k867112
59.5k867112
add a comment |
add a comment |
Chuckster is a new contributor. Be nice, and check out our Code of Conduct.
Chuckster is a new contributor. Be nice, and check out our Code of Conduct.
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So, it seems that you are really just trying to come up with a new compression algorithm? From what I can tell, JPEG implementations will try and pad images that do not have 8 x 8 (or whatever the block size is) blocks evenly.
– Tyler Nichols
Mar 21 at 15:13
Is it possible to convert 1D -> 2D by stacking up subsets and then splitting them up to get result?
– Tyler Nichols
Mar 21 at 15:17
I am not sure if folding the data after the 8th column (to create blocks that are the power of 8) would affect the accuracy of the compression since the data doesn't have any such property. I was thinking to maybe create 2D version of the data by adding just 0s to create 8 more rows. I guess multiplying with 0s would not particularly effect the performance. Am I making any sense?
– Chuckster
Mar 21 at 15:55