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首页多媒体信号处理:新兴技术与应用概述
多媒体信号处理:新兴技术与应用概述
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更新于2024-07-22
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多媒体信号处理是一门涵盖了数字图像与视频处理的新兴领域和关键技术。它结合了信息理论、信号处理、电子与光电子系统以及计算机科学与微处理器技术(包括专用的数字信号处理器DSP)。随着新信息技术的兴起,这一领域发展迅速,其核心在于数学方法的应用,这些方法既包括随机应变的即兴策略,也包括经过深入研究和建立的系统化方法。 在数字图像处理方面,目标是通过改进图像质量、实现比特压缩编码来减小数据大小,或者从图像中提取信息。这个过程涉及到一系列技术,如图像增强、噪声消除、边缘检测、特征提取等,这些都是为了满足日益增长的在医学成像、工业质量控制、安全监控、艺术与娱乐等多个领域的应用需求。 早期的数字图像处理主要依赖于数学工具,如线性代数、傅立叶变换、概率论和统计学,以及信号分析和滤波。此外,专用的数字信号处理器(DSP)的出现极大地推动了处理速度和能力的提升,使得实时图像处理成为可能。现代计算机视觉技术,如深度学习和机器学习,也在不断丰富和优化图像处理算法,使得系统能够自动识别和理解图像内容。 多媒体信号处理是一门交叉学科,它融合了基础理论与前沿技术,是现代科技发展的关键驱动力之一。随着技术的进步,我们可以期待更多创新的图像和视频处理解决方案,以适应不断变化的信息社会需求。学习这门技术,无论是对于科研人员、工程师还是创业者,都具有重要的实用价值和前瞻性。
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2005 D. BARBA 7
Basic Image/Video Properties
• Image/video signal is a 2-D/2-D+t scalar/vectorial signal which is
complex:
• Non stationary
• Non Gaussian
• Non isotropic
• Two (image) or three (video) main features
– Contours: abrupt change in some important characteristics
– Texture: spatial variation of the 2-D signal apart its local mean value
(mean value, texture description)
Edges are locally 1-D signals
– Motion: in case of video (time-varying image sequence)
An image is a 2D scalar (grayscale image) or vectorial (color image for example) signal.
Video which is a succession of images ordered temporally is a 2-D+t (t: time) scalar (gray-
scale video) or vectorial (color video) signal.
The "Image" signal is complex because it is:
- non-stationary: its contents in space frequencies change with the space
coordinates;
- non-Gaussian: its statistical properties do not follow a Gaussian probability law;
- non-isotropic: the properties of the image signal are not the same ones with the
orientation (e.g. in the images taken on the ground, the horizontal and vertical
directions are more frequent for contours than the oblique directions).
The classical methods and tools used in signal processing are often designed for stationary,
Gaussian or isotropic signals (e.g. Discrete Fourier Transform). They cannot be directly
applied to images.
Incidentally, images are mainly characterized by two types of element, namely contour and
texture:
- Contours are abrupt change of important characteristics from an area A to an area
B of a scene (average value, texture description). The edges can be locally
considered as 1D signals;
- Textures are spatial variation of the 2D signal apart its local mean value;
- Motion of the objects in a scene involves temporal modifications in the successive
frames of a video.
Now you have seen a general overview of images and digital image processing. In the
next part of this chapter, we will look at methods for representing images (digitizing and
encoding), which must be used in order to carry out digital processing. We will also see some
concrete examples of results relating to the domains of application that we explored earlier.
2005 D. BARBA 1
Examples of Image Processing
Images and Videos Analysis
Chapter 1
MULTIMEDIA SIGNAL PROCESSING
The four major domains of application for image processing have been globally
presented: what are the issues? what are the objectives? what methods to use? and which
tools? We will now look more closely at some concrete applications derived from these
different domains.
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