Arithmetic Coding + Statistical Modeling = Data Compression. This article first appeared in the. February, 1. 99. 1 issue of Dr. Dobb’s Journal. Update: I have a substantially improved article that covers Arithmetic Coding only which you can find here: Data Compression With Arithmetic Coding. I strongly encourage you to read this article first for an improved take on the topic. Note: This article was originally published in two parts. Both parts have been combined here into one post – please note that when you reach the footnotes and attachments for the first part, you are only halfway through the article. In the world of small systems, dictionary based data compression techniques seem to be more popular at this time. However, by combining arithmetic coding with powerful modeling techniques, statistical methods for data compression can actually achieve better performance. Registrations are now closed This event has completed. Come back next year for ADUG Symposium 2017. Look out for the Early Bird Discount and save on the registration fee. Ten years ago I issued a simple challenge to the compression community: reduce the size of roughly half a megabyte of random data – by as little as one byte – and. Update:I have a substantially improved article that covers Arithmetic Coding only which you can find here: Data Compression With Arithmetic Coding. This article describes how to use DirectShow.NET in VB.NET; Author: Jarno Burger; Updated:; Section: Audio and Video; Chapter: Multimedia; Updated: 26 Apr. By: David Wahlman of Wahlman Photography. Recently I was asked about the process of converting images to black & white; namely when to know the image would be good. Academia.edu is a platform for academics to share research papers. While VB Migration Partner can often automatically translate most VB6 constructs, in some cases it is necessary for you to either modify the VB6 code before. Technology keeps you connected everywhere you go, helps you capture every moment & makes your life a bit easier; stay up-to-date with tips & tricks from eHow. Search for a text string in a column and return multiple adjacent values; Search for a text string in a column and return multiple adjacent values. This two- part article discusses how to combine arithmetic coding with several different modeling methods to achieve some impressive compression ratios. The first part of the article details how arithmetic coding works. The second shows how to develop some effective models that can use an arithmetic coder to generate high performance compression programs. Terms of Endearment. Data compression operates in general by taking symbols from an input text, processing them, and writing codes to a compressed file. For the purposes of this article, symbols are usually bytes, but they could just as easily be pixels, 8. EBCDIC characters. To be effective, a data compression scheme needs to be able to transform the compressed file back into an identical copy of the input text. Needless to say, it also helps if the compressed file is smaller than the input text! Dictionary based compression systems operate by replacing groups of symbols in the input text with fixed length codes. A well- known example of a dictionary technique is LZW data compression. LZW operates by replacing strings of essentially unlimited length with codes that usually range in size from 9 to 1. Statistical methods of data compression take a completely different approach. They operate by encoding symbols one at a time. The symbols are encoded into variable length output codes. The length of the output code varies based on the probability or frequency of the symbol. Low probability symbols are encoded using many bits, and high probability symbols are encoded using fewer bits. In practice, the dividing line between statistical and dictionary methods is not always so distinct. Some schemes can’t be clearly put in one camp or the other, and there are always hybrids which use features from both techniques. However, the methods discussed in this article use arithmetic coding to implement purely statistical compression schemes. Huffman Coding: The Retired Champion. It isn’t enough to just be able to accurately calculate the probability of characters in a datastream, we also need a coding method that effectively takes advantage of that knowledge. Probably the best known coding method based on probability statistics is Huffman coding. Huffman published a paper in 1. The Huffman code table was guaranteed to produce the lowest possible output bit count possible for the input stream of symbols, when using fixed length codes. Huffman called these minimum redundancy codes, but the scheme is now universally called Huffman coding. Other fixed length coding systems, such as Shannon- Fano codes, were shown by Huffman to be non- optimal. Huffman coding assigns an output code to each symbol, with the output codes being as short as 1 bit, or considerably longer than the input symbols, strictly depending on their probabilities. The optimal number of bits to be used for each symbol is the log base 2 of (1/p), where p is the probability of a given character. Thus, if the probability of a character is 1/2. If the probability goes up to 1/2, the optimum number of bits needed to code the character would go down to 1. The problem with this scheme lies in the fact that Huffman codes have to be an integral number of bits long. For example, if the probability of a character is 1/3, the optimum number of bits to code that character is around 1. The Huffman coding scheme has to assign either 1 or 2 bits to the code, and either choice leads to a longer compressed message than is theoretically possible. This non- optimal coding becomes a noticeable problem when the probability of a character becomes very high. If a statistical method can be developed that can assign a 9. The Huffman coding system would probably assign a 1 bit code to the symbol, which is 6 times longer than is necessary. Adaptive Schemes. A second problem with Huffman coding comes about when trying to do adaptive data compression. When doing non- adaptive data compression, the compression program makes a single pass over the data to collect statistics. The data is then encoded using the statistics, which are unchanging throughout the encoding process. In order for the decoder to decode the compressed data stream, it first needs a copy of the statistics. The encoder will typically prepend a statistics table to the compressed message, so the decoder can read it in before starting. This obviously adds a certain amount of excess baggage to the message. When using very simple statistical models to compress the data, the encoding table tends to be rather small. For example, a simple frequency count of each character could be stored in as little as 2. This wouldn’t add significant length to any except the very smallest messages. However, in order to get better compression ratios, the statistical models by necessity have to grow in size. If the statistics for the message become too large, any improvement in compression ratios will be wiped out by added length needed to prepend them to the encoded message. In order to bypass this problem, adaptive data compression is called for. In adaptive data compression, both the encoder and decoder start with their statistical model in the same state. Each of them process a single character at a time, and update their models after the character is read in. This is very similar to the way most dictionary based schemes such as LZW coding work. A slight amount of efficiency is lost by beginning the message with a non- optimal model, but it is usually more than made up for by not having to pass any statistics with the message. The problem with combining adaptive modeling with Huffman coding is that rebuilding the Huffman tree is a very expensive process. For an adaptive scheme to be efficient, it is necessary to adjust the Huffman tree after every character. Algorithms to perform adaptive Huffman coding were not published until over 2. Huffman coding was first developed. Even now, the best adaptive Huffman coding algorithms are still relatively time and memory consuming. Arithmetic Coding: how it works. It has only been in the last ten years that a respectable candidate to replace Huffman coding has been successfully demonstrated: Arithmetic coding. Arithmetic coding completely bypasses the idea of replacing an input symbol with a specific code. Instead, it takes a stream of input symbols and replaces it with a single floating point output number. The longer (and more complex) the message, the more bits are needed in the output number. It was not until recently that practical methods were found to implement this on computers with fixed sized registers. The output from an arithmetic coding process is a single number less than 1 and greater than or equal to 0. This single number can be uniquely decoded to create the exact stream of symbols that went into its construction. In order to construct the output number, the symbols being encoded have to have a set probabilities assigned to them. For example, if I was going to encode the random message “BILL GATES”, I would have a probability distribution that looks like this. Character Probability. SPACE 1/1. 0. A 1/1. 0. B 1/1. E 1/1. 0. G 1/1. I 1/1. 0. L 2/1. S 1/1. 0. T 1/1. Once the character probabilities are known, the individual symbols need to be assigned a range along a probability line, which is nominally 0 to 1. It doesn’t matter which characters are assigned which segment of the range, as long as it is done in the same manner by both the encoder and the decoder. The nine character symbol set use here would look like this. Character Probability Range. SPACE 1/1. 0 0. A 1/1. 0 0. B 1/1. 0 0. E 1/1. 0 0. G 1/1. 0 0. I 1/1. 0 0. L 2/1. 0 0. S 1/1. 0 0. T 1/1. 0 0. Each character is assigned the portion of the 0- 1 range that corresponds to its probability of appearance. Note also that the character “owns” everything up to, but not including the higher number. When encoding the message “BILL GATES”, the first symbol is “B”. In order for the first character to be decoded properly, the final coded message has to be a number greater than or equal to 0. What we do to encode this number is keep track of the range that this number could fall in. So after the first character is encoded, the low end for this range is 0. After the first character is encoded, we know that our range for our output number is now bounded by the low number and the high number. What happens during the rest of the encoding process is that each new symbol to be encoded will further restrict the possible range of the output number. The next character to be encoded, . If it was the first number in our message, we would set our low and high range values directly to those values. So what we do instead is say that . This means that the new encoded number will have to fall somewhere in the 5. Applying this logic will further restrict our number to the range 0. The algorithm to accomplish this for a message of any length is is shown below. Set high to 1. 0. While there are still input symbols do. We find the first symbol in the message by seeing which symbol owns the code space that our encoded message falls in. Webcam using Direct. Show. NET - Code. Project. Introduction. This article describes how to use Direct. Show. NET. Direct. Show. NET is a dll to use Direct. Show as managed code. I found it hard to find examples for using Direct. Show. I still didn't find out how that all works. That is why I translated a C# example of Direct. Show. NET to VB. NET code. Here, I show you what the code finally looks like. You all could still help me (and others) to provide a better understanding of what the code means. In the help below, you will only find stuff that I thought was difficult for me to understand. The rest is explained in the code itself. In the meanwhile, I recommend the book . I also recommend googling for Direct. Show. NET and reading their website which is really good. Turn off Enable Application Framework, and choose Directshow. Samples. Form. 1 as the startup object. Be sure to have NET 2. You should download the code before reading this article. Step 1. Imports System. Imports System. Diagnostics. Imports System. Drawing. Imports System. Runtime. Interop. Services. Imports System. Windows. Forms. Imports Direct. Show. Lib. Imports System. Runtime. Interop. Services. Com. Types. Nothing special here. Step 2. Namespace Capture. Public means that outside this namespace , this class is still reachable. Inherits means something like in MSDN : causes the current class or interface to inherit the attributes, variables, properties, procedures, and events from another class or set of interfaces. So, go and let this class feel like system. Step 3. Inside the class, there are four parts: Setting variables / objects to use in this class Our main program loop The main functions / routines we use Helper functions Step 4. A: Setting variables. Enum Play. State. Stopped = 0. Paused = 1. Running = 2. Init = 3. End. Enum. Dim current. State As Play. State = Play. State. Stopped So what does this do ? Let's give a example : If. Me. Current. State = Play. State. Paused. Then. Me. Current. State = Play. State. Running This looks a lot nicer than: If. Me. Current. State = 0. Then. Me. Current. State = 3. Dim D As. Integer = Convert. To. Int. 32(. And that it has to start in place 0. X8. 00. 0, because that place is where the filtergraph events start. Filtergraph events are events that Direct. Show gives you when you use inputs, filters and outputs. Dim video. Window As IVideo. Window = Nothing. What you do here is create an object with the format of a videowindow that starts out empty (with nothing in it). Generally, this is a video renderer that draws the video onto a window on the display. Dim media. Control As IMedia. Control = Nothing. This creates an empty object/interface that function likes tape- deck buttons. The filter graph exposes the IMedia. Control interface to allow applications to control the streaming of media through the filters in the graph. The interface provides methods for running, pausing, and stopping the streaming of data. Dim media. Event. Ex As IMedia. Event. Ex = Nothing. This creates a empty object for event messages. This interface is used by applications to receive notification that an event has occurred. Applications can then avoid using a separate thread that waits until an event is set. Dim graph. Builder As IGraph. Builder = Nothing. This is our main object that will create filters. It will put the input filter (webcam), through a conversion filter, so that it can show it on a Ivideowindow. This interface provides methods that enable an application to build a filter graph. The Filter Graph Manager implements this interface. Dim capture. Graph. Builder As ICapture. Graph. Builder. 2 = Nothing. This is a object that we create to help us out with building stuff that has to do with capturing of video and/or audio. Start graphedit. exe and go to File- > Connect to remote graph. What would happen is that graphedit makes a graphical representation of how it creates your filters to show . Step 4. B: Our main program loop. This is a short one: < STAThread()> Shared. Sub < place w: st=. That's rather handy , because streaming can be rather more complicated if you can't think about this step by step. Think about what could happen between the window and the capture preview if they both live their own life. Then moving the main window could leave your capture preview behind because the capture preview is still busy with its own . Sub main is the main/head sub- routine that will start when we write code. Shared Sub Main means that if our class is used multiple times in a new program/object, we still only use one Sub Main that will be shared by all. There are no extra copies of the sub main in memory for each instance, there is only one. Application. Run() starts an application , a . This use of the resource. Manager gives access to the resource management of the form. Next interesting line is the Debug. Writeline. It writes a line of text to your debug output. If you don't know where that is , go to the Visual Basic menu, go to debug, and select output. When you test run your program, you will see these messages appearing in this output window. Public. Sub Capture. Video(). Dim source. Filter As IBase. Filter = Nothing. Try. Big chunk of code. Catch ex As Exception. Message. Box. Show(. We will try to implement the code . When an error occurs, either the system or the currently executing application reports it by throwing an exception containing information about the error. It will keep them as numbers. So you have to use a error number translator. I have shown how to do this later in the code. Next we create an object that works like a . These objects have a input- pin and output- pin, and do filtering in between. Direct. Show graphs are (in the most simplest way) a chain of filter- objects , each doing their own type of conversion or filtering. Now we use this filter object creation to create the source (our webcam). Filter objects do more, but I won't tell you now to keep it simple. Get. Interfaces()This means we will start a subroutine to create the building blocks of our interface. CTYPE is a function to convert a object type to another object type. Me. graph. Builder = CType(New Filter. Graph, IGraph. Builder) Lets fill the . Me. capture. Graph. Builder = CType(New Capture. Graph. Builder. 2, ICapture. Graph. Builder. 2Let's fill the . Me. video. Window = CType(Me. Builder, IVideo. Window)Let's fill the . Me. media. Event. Ex = CType(Me. graph. Builder, IMedia. Event. Ex)Let's fill the . Remember that when there is an error , the . When there is an error we throw a exception. Let's look at the function . A sermonizer creates a . Enumerations provide a convenient way to work with sets of related constants and to associate constant values with names. For example, you can declare an enumeration for a set of integer constants associated with the days of the week, and then use the names of the days rather than their integer values in your code. Enumerations most often count objects in the most abstract way possible. An enumerator is an object that iterates through its associated collection. It can be thought of as a movable pointer to any element in the collection. Dim source As. Object = Nothing. Create a empty object called . It puts them in dev. Enum. The zero at the end means that we will check up every sort of filter (to find Video. Input. Devices). Marshal. Release. Com. Object(dev. Enum)The device enumerator is no more needed so we dump it. Marshal provides a collection of methods for allocating unmanaged memory, copying unmanaged memory blocks, and converting managed to unmanaged types, as well as other miscellaneous methods used when interacting with unmanaged code. If class. Enum Is. Nothing. Then. Throw. New Application. Exception(. The sample will now close. So, let's check if we have one, otherwise we don't have a webcam. If class. Enum. Next(moniker. Length, moniker, Int. Ptr. Zero) = 0. Then. Dim iid As Guid = Get. Type(IBase. Filter). GUID. moniker(0). Bind. To. Object(Nothing, Nothing, iid, source). Else. Throw. New Application. Exception(. Imonkier. So Classenum. next let moniker fill with only one element of classenum (that will be the first videoinputdevice). And if this classenum gives back a value 0 , then. Marshal. Release. Com. Object(moniker(0)). Marshal. Release. Com. Object(class. Enum) Dump the objects. Ok, so everything went fine in finding a capture device, and now that we have a source- filter inside . We let it build the rest of our filtergraph for us. There are five variables as you see. Marshal. Release. Com. Object(source. Filter)The . Setup. Video. Window()Let's check that sub routine out. Public. Sub Setup. Video. Window(). Dim hr As. Integer = 0. hr = Me. Video. Window. put. Meaning : set the video window to be a child of the main window. Resize. Video. Window : we check that out later. Me. Current. State = Play. State. Running. Debug. Write. Line(. But what to do when the form resizes ? For us, it is interesting what to do when the form is minimized or normal. Because the state of the directshow preview could better change in those situations. That's why we start out a function called Change. Preview. State(). The code of Resize. Video. Window is already explained above. I will not explain Change. Preview. State() because it is really simple. Protected. Overloads. Sub Wnd. Proc(By. Ref m As Message). Select. Case m. Msg. Case WM. That something is Wnd. Proc, the message interface so that we can see messages that we need to know for our program. It is used by. Ref because we make a reference to that message. In case the message is a WM. But if it is not the case, we want to restore the message and sent it back to where it belongs. That's what the rest means. Public. Sub Handle. Graph. Event(). Dim hr As. Integer = 0. Dim ev. Code As Event. Code. Dim ev. Param. 1 As. Integer. Dim ev. Param. As. Integer. If. Me. Media. Event. Ex Is. Nothing. Then. Return. End. If. While. Me. Media. Event. Ex. Get. Event(ev. Code, ev. Param. 1, ev. Param. Me. Media. Event. Ex. Free. Event. Params(ev. Code, ev. Param. 1, ev. Param. 2). Ds. Error. Throw. Exception. For. HR(hr). End.
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Official Music video for 'Hisingen Blues' from the GRAVEYARD SUBSCRIBE to Graveyard YouTube. Hisingen Blues, out on March 25 (Europe) and April 19. Herbert pfostl's paper graveyard 4/11/16. The light that never was. It is utterly gone out of the world as the song of a destroyed wild bird. VAN GRAVEYARD CHRONICLING THE RICH. Shag,mirrors,gold vein mirrors,lucite bar top that lights. Vans on this site are in and out of the yards in 2 to 3 weeks. Graveyard was featured on Rolling Stone Magazine's Fricke's Picks for their first ever US gig at SXSW. Lights Out: Released: October 26, 2012 (Europe). Graveyard – Lights Out (2012) Tuesday, September 20, 2016. Content feed; Comments Feed; Home. Artist: Graveyard Album: Lights Out Released: 2012. Graveyard - Graveyard . Greetings folks, Feel free to stop by and check out some of the goodies that have passed through my. Howard Hewett Show Me Mp. Download - Fullsongs. Discover Howard Hewett's full discography. 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