Wavelet, a C++ class library for Wavelet transforms on images.

Compression that is optimised for images containing low amounts of data. The relatively inferior image quality is offset against the low bandwidth demands on transmission mediums.

Wavelet compression works by analyzing an image and converting it into a set of mathematical expressions that can then be decoded by the receiver. Wavelet compression is scalable, depending on the features of the encoding application.

This is an oscillating waveform that only lasts for a few cycles. A natural wave continues indefinitely.

This type of image compression is mainly used for single images and not video streams. Because it's superior to JPEG compression, it is however used in some video surveillance codecs, though there isn't a universally adopted standard for usage of this codec.

A mathematical algorithm that is used to efficiently compress and decompress the phase & frequency information that is contained in a transmitted signal.

A new file format that provides storage of photo-realistic images. Most similar to JPEG.

a member of a family of oscillatory scaleable functions which deviates from zero within a limited spatial regime, and has zero normalization

a small wave set in a limited time that grows and decays, as distinguished from the big wave which is a sine wave that keeps on oscillating up and down

a statement of balance and memory of experiences that is energy efficient

a very simple class of mathematical transform s to apply to a signal or other chunk of data , typically for the purpose of compression or analysis or the like

a waveform of effectively limited duration that a has an average value of zero

A particular type of video compression that is especially suitable for CCTV. Offers higher compression ratio with equal or better quality to JPEG.

A wavelet is a mathematical function useful in signal processing and image compression.

Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale.

A mathematical function useful in digital signal processing and image compression. In the Internet communications, wavelet has been used to compress images to a greater extent than is generally possible with other methods such as JPEG or MPEG.

A member of a family of functions generated by taking translations [e.g., () â†’ ( + 1)] and scalings [e.g., () â†’)] of a function (), called the "mother" wavelet. The choice of () is limited by the condition that the square of () be integrable over all . Linear combinations of wavelets are used to represent wavelike signals. The wavelet decomposition of a signal offers an advantage over the Fourier decomposition in that local or short-term contributions to the signal can be better represented.

A wavelet is a function which (a) maps from the real line to the real line, (b) has an average value of zero, (c) has values very near zero except over a bounded domain, and (d) is used for the purpose, analogous to Fourier analysis, implied by the following paragraphs. Unlike sine waves, wavelets tend to be irregular, asymmetric, and to have values that die out to zero as one approaches positive and negative infinity. "Fourier analysis consists of breaking up a signal into sine waves of various frequencies. Similarly, wavelet analysis is the breaking up of a signal into shifted and scaled versions of the original (or mother) wavelet." By decomposing a signal into wavelets one hopes not to lose local features of the signal and information about timing. These contrast with Fourier analysis, which tends to reproduce only repeated features of the original function or series. Source: econterms

In mathematics, wavelets, wavelet analysis, and the wavelet transform refers to the representation of a signal in terms of a finite length or fast decaying oscillating waveform (known as the mother wavelet). This waveform is scaled and translated to match the input signal. In formal terms, this representation is a wavelet series, which is the coordinate representation of a square integrable function with respect to a complete, orthonormal set of basis functions for the Hilbert space of square integrable functions.