Why create a Huffman tree per character instead of a Node?
For a school assignment we’re supposed to make a Java implementation of a compressor/decompresser using Huffman’s algorithm.
Does it matter the direction of a Huffman’s tree child node?
So, I’m on my quest about creating a Java implementation of Huffman’s algorithm for compressing/decompressing files (as you might know, ever since Why create a Huffman tree per character instead of a Node?) for a school assignment.
How to discriminate from two nodes with identical frequencies in a Huffman’s tree?
Still on my quest to compress/decompress files with a Java implementation of Huffman’s coding (http://en.wikipedia.org/wiki/Huffman_coding) for a school assignment.
How should I compress a file with multiple bytes that are the same with Huffman coding?
On my great quest for compressing/decompressing files with a Java implementation of Huffman coding (http://en.wikipedia.org/wiki/Huffman_coding) for a school assignment, I am now at the point of building a list of prefix codes. Such codes are used when decompressing a file. Basically, the code is made of zeroes and ones, that are used to follow a path in a Huffman tree (left or right) for, ultimately, finding a byte.
How do I find average bits per symbol using huffman code?
I’m trying to write a program in c for Huffman coding, but I am stuck. For input I have:
Encode Optimal Huffman code
I have given message encoded with non-optimal Huffman code. I need to decode the message and encode it again, but this time with optimal Huffman code, so after that I can find average_number_of_bits_per_symbols = num_of_bits_in_message / num_of_characters_in_message
Encode Optimal Huffman code
I have given message encoded with non-optimal Huffman code. I need to decode the message and encode it again, but this time with optimal Huffman code, so after that I can find average_number_of_bits_per_symbols = num_of_bits_in_message / num_of_characters_in_message
Encode Optimal Huffman code
I have given message encoded with non-optimal Huffman code. I need to decode the message and encode it again, but this time with optimal Huffman code, so after that I can find average_number_of_bits_per_symbols = num_of_bits_in_message / num_of_characters_in_message
Encode Optimal Huffman code
I have given message encoded with non-optimal Huffman code. I need to decode the message and encode it again, but this time with optimal Huffman code, so after that I can find average_number_of_bits_per_symbols = num_of_bits_in_message / num_of_characters_in_message
Calculating uncompressed file size without uncompressing file in zlib
I am writing a python program which parses zip (currently only zlib, using DEFLATE compression) files and verifies the correctness of their headers and data. One of the things I’m trying to achieve is calculating the uncompressed size of a compressed (DEFLATE-d) file inside a zip archive, without actually uncompressing the file and, obviously, not relying on the uncompressed size field found in the file record’s headers. This is so that I can ensure that none of the zip record’s fields have been tampered with (in this case, the uncompressed size field).