huffman-code

问题 Can someone help me figure out where I'm getting this error. I know it's probably a double deletion or something like this. For the background this is an implementation of the huffman's tree as you can easily realize on wikipedia. CharCountNode class implementation int main() { ifstream input; input.open("input.txt"); MinPriorityQueue<CharCountNode> heap; map<char, int> m; while(input.good()) m[input.get()] += 1; for( map<char, int>::const_iterator it = m.begin(); it != m.end(); ++it ) heap

问题 I want to save Huffman codes into a file. How can I do this? I am saving Huffman codes into a string but size of generated file is bigger than Original file. 回答1: A very simple approach is to write one bit at a time with something like the following: unsigned char acc; // Accumulator of bit waiting to be written int bitcount; // How many bits are aready present in the accumulator // write a single bit (0/1) void writebit(int bit) { acc |= (bit << bitcount); if (++bitcount == 8) { writebyte

问题 Hello I am trying to implement Canonical huffman encoding but i dont understand wiki and google guides, I need explain more abstractly... I tried this: 1. Get list of regular huffman encoding length's codes. like this: A - code: 110, length: 3. B - code: 111, length: 3. C - code: 10, length 2. D - code: 01, length 2. E - code: 00, length 2. I sorting the table by symbol and length like this: C - code: 10, length 2. D - code: 01, length 2. E - code: 00, length 2. A - code: 110, length: 3. B -

问题 I'm trying to understand compression in PNG - but I seem to find a lot of contradictory information online ... I would like to understand - how is searching done in the LZ77-part: hash table with linked lists? is this defined in deflate? or implemented in zlib? is there a choice of the search method? - can PNG encoders/decoders set some parameters for the compression (strategy, filter, etc.) or is there a default for PNG? - does the LZ77-part do greedy or lazy evaluation? or is this an option

问题 I am told that Huffman coding is used as loseless data compression algorithm , but I am also told that real data compress software do not employ Huffman coding, because if the keys are not distributed decentralized enough, the compressed file could be even larger than the orignal file. This leaves me wondering are there any real-world application of Huffman coding? 回答1: Huffman is widely used in all the mainstream compression formats that you might encounter - from GZIP, PKZIP (winzip etc)

问题 I'm trying to solve a Huffman Coding problem, but I'm not completely sure I understand the topic completely. I am trying to figure out if the following are is a valid Huffman Code: A: 0 B: 01 C: 11 D: 110 E: 111 What I'm thinking is that it is not valid, because A, or 1, would infringe on B, or 01. I'm not positive though. Could someone enlighten me on this? Edit: I'm sorry I meant to type A as 0 and not 1. 回答1: No. A Huffman code is a prefix code, which means that no code can be a prefix of

问题 A Huffman table, in JPEG standard, is generated from a collection of statistics in two steps. One of the steps is implementing function/method given by this picture: (This picture is given in Annex K of JPEG standard): Problem is here. Previously in standard (Annex C) says this sentence: Huffman tables are specified in terms of a 16-byte list (BITS) giving the number of codes for each code length from 1 to 16. This is followed by a list of the 8-bit symbol values (HUFFVAL), each of which is

问题 I read a sentence that the Height of Huffman Tree with 10-Input Symbol with Frequence 1 to 10 is 5 !! i do lots of study but i couldn't get it very clear and how we calculate the Height of tree !! any idea? 回答1: I don't usually see the term "height", but rather "depth". In any case, they mean the number of bits of the longest code. That is in fact equal to five for the frequencies you quote. 来源： https://stackoverflow.com/questions/28833747/huffman-height-calculation-and-some-challenges

问题 I have a problem simlar to Huffman's encoding, I'm not sure exactly how it can be solved or if it is a reverse Huffman's encoding. But it definitely can be solved using a greedy approach. Consider a set of length, each associated with a probability. i.e. X={a1=(100,1/4),a2=(500,1/4),a3=(200,1/2)} Obviously, the sum of all the probabilities = 1. Arrange the lengths together on a line one after the other from a starting point. For example: {a2,a1,a3} in that order from start to finish. Define

问题 I have implemented the Huffman Encoding Algorithm in Java using Priority Queues where I traverse the Tree from Root to Leaf and get encoding example as #=000011 based on the number of times the symbol appears in the input. Everything is fine, the tree is being built fine, encoding is just as expected: But the output file I am getting is bigger size than the original file. I am currently appending '0' & '1' to a String on traversing left node and right node of the tree. Probably what I end up