DCT algorithm for image compression?
608077
1. plug in Ipod tune "I got rhythm" and play it on a loop.\n2. Take the converse of the algorithm and divde by the beta weight that accounts for the most various in the equation.\n3. Eat a sandwhich... this is hard!\n4. Load images and begin decompression process.\n5. Defragment any non-algorithim friendly data bits (or  kibbles)\n6. Drink an orange soda or something with some carbonation for god's sake (and call your mother)\n7. Plug is DVR-read/write and enjoy your freshly baked and only slightly compressed images.  Voila!
725484
I recommend ACD See. It's user friendly and can convert all of your GIFS to JPEGS all at once (depends on how fast your computer is). Just go to www.acdsystems.com/products and you can download a trial version of it. It's fun to use for those who scan their comics and just read them in their computer.
109519
There is by definition, two ways to compress any type of data:\n1. Lossy\n2. Lossless\n\nMost sound compression algorithms use lossy compression to compress the sound data.  It is reasonable to achieve 10x compression with little noticable loss of sound quality using a popular compression method such as MP3 or the more recent MP4 (which are actually both substandards of the MPEG specifications, for use in compressing video (moving picture) data).  The MPEG specs use a psycho-acoustic modelling technique in order to remove parts of the sound that are not noticable based on the limitations of human hearing.  For example, in a loud passage, a soft background sound will not be heard clearly and thus can be encoded using less bits.  There are also various ways of doing the encoding, using a fixed bit bucket (known as constant bit rate) or using a variable bit bucket, where bits can be traded based on time so that passages that are tougher to encode can use more bits (variable bit rate).\n\nLossless compression techniques generally fall under the same category as general compression algorithms such as those used for zipping files, etc.  However, sound does have certain characteristics that when exploited will allow better compression than a standard zipping of the PCM data would allow.  A good explanation of this type of technique can be found on the website linked below.  Because of the inherent randomness in sound data, typical lossless compression rates are about 2X.
1050888
Picasa...free jpeg format software download from Google.\nWalmart.com Photo Center
556966
You may have to experiment a bit.  You see, depending on the number of COLORs that appear in your photo, the compression will vary from photo to photo.   But use the RESIZE feature of your graphic program.    CROP before REDUCE, then use SAVE AS, so you still have the original. \n\nRemember, every time you edit a JPG file, it loses detail and resolution, so GO BACK to the original when you want to make a different rendering or size.
1176229
There are lot of softwares for this kind of Job. You can try "ImTOOMpeg Encorder". It can convert lots of different file types.
849482
Have you thought about using FFT (Fast Fourier Transform)? That should be easy to implement.
417788
Use NeroVision express..\nThe movie automatically gets compressed according to the requirements with almost zero quality reduction.
320469
yes u need graphic software like adobe photoshop, ulead photoimpact, corel paintshop pro or simply ACD see but it depends on the format of the picture, is it jpg, gif or psd,....etc!!\nthen u need a compression way... the most lossless method is the LZW or alike ... u need strong software like adobe Photshop to do so..
237487
Formally, the discrete cosine transform is a linear, invertible function F : RN -> RN (where R denotes the set of real numbers), or equivalently an N × N square matrix. There are several variants of the DCT with slightly modified definitions. The N real numbers x0, ..., xN-1 are transformed into the N real numbers X0, ..., XN-1. \n\nDCT-I\n \nSome authors further multiply the x0 and xN-1 terms by √2, and correspondingly multiply the X0 and XN-1 terms by 1/√2. This makes the DCT-I matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT.\n\nThe DCT-I is exactly equivalent (up to an overall scale factor of 2), to a DFT of 2N − 2 real numbers with even symmetry. For example, a DCT-I of N=5 real numbers abcde is exactly equivalent to a DFT of eight real numbers abcdedcb (even symmetry), divided by two. (In contrast, DCT types II-IV involve a half-sample shift in the equivalent DFT.)\n\nNote, however, that the DCT-I is not defined for N less than 2. (All other DCT types are defined for any positive N.)\n\nThus, the DCT-I corresponds to the boundary conditions: xn is even around n=0 and even around n=N-1; similarly for Xk.\n\nDCT-II\n \nThe DCT-II is probably the most commonly used form, and is often simply referred to as "the DCT".\n\nThis transform is exactly equivalent (up to an overall scale factor of 2) to a DFT of 4N real inputs of even symmetry where the even-indexed elements are zero. That is, it is half of the DFT of the 4N inputs yn, where y2n = 0, y2n + 1 = xn for , and y4N − n = yn for 0 < n < 2N.\n\nSome authors further multiply the X0 term by 1/√2 (see below for the corresponding change in DCT-III). This makes the DCT-II matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT of half-shifted input.\n\nThe DCT-II implies the boundary conditions: xn is even around n=-1/2 and even around n=N-1/2; Xk is even around k=0 and odd around k=N.\n\nDCT-III\n \nBecause it is the inverse of DCT-II (up to a scale factor, see below), this form is sometimes simply referred to as "the inverse DCT" ("IDCT").\n\nSome authors further multiply the x0 term by √2 (see above for the corresponding change in DCT-II). This makes the DCT-III matrix orthogonal (up to a scale factor), but breaks the direct correspondence with a real-even DFT of half-shifted output.\n\nThe DCT-III implies the boundary conditions: xn is even around n=0 and odd around n=N; Xk is even around k=-1/2 and odd around k=N-1/2.\n\nDCT-IV\n \nThe DCT-IV matrix is orthogonal (up to a scale factor).\n\nA variant of the DCT-IV, where data from different transforms are overlapped, is called the modified discrete cosine transform (MDCT).\n\nThe DCT-IV implies the boundary conditions: xn is even around n=-1/2 and odd around n=N-1/2; similarly for Xk.\n\nDCT V-VIII\nDCT types I-IV are equivalent to real-even DFTs of even order. In principle, there are actually four additional types of discrete cosine transform (Martucci, 1994), corresponding to real-even DFTs of logically odd order, which have factors of N+1/2 in the denominators of the cosine arguments. However, these variants seem to be rarely used in practice.\n\n(The trivial real-even array, a length-one DFT (odd length) of a single number a, corresponds to a DCT-V of length N=1.)\n\nInverse transforms\nThe inverse of DCT-I is DCT-I multiplied by 2/(N-1). The inverse of DCT-IV is DCT-IV multiplied by 2/N. The inverse of DCT-II is DCT-III multiplied by 2/N (and vice versa).\n\nLike for the DFT, the normalization factor in front of these transform definitions is merely a convention and differs between treatments. For example, some authors multiply the transforms by  so that the inverse does not require any additional multiplicative factor.\n\nComputation\nAlthough the direct application of these formulas would require O(N2) operations, it is possible to compute the same thing with only O(N log
795880
Right click on the image file and select Properties.\nThis will give you the size of the image.\nHow small? How long is a piece of string?\nIf you compress a small file it is possible to finish up with a larger one as the symbols are being used.
511932
that would require an animated gif image. i don't beleive you can use anything but a jpeg.
697514
Faster more efficient reproduction - no suurprises
1024320
Try Picasa (free). Download here:
122830
mpeg..avi...rmvb..torent..
402935
Random computer generation to ensure a high contrast between neighboring colors
331707
search for CBIR on google u will get a no of resources. I had done one project related to this in c++. if u need any help mail me