Understanding Orthogonal Projection in Linear Operators

In summary, an orthogonal projection onto its image is a projection that sends every vector in the image of T to a vector in the projection.
  • #1
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Let T in L(V) be an idempotent linear operator on a finite dimensional inner product space. What does it mean for T to be "the orthogonal projection onto its image"?
 
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  • #2
Every element in v is a combination e+f where e is in the image of T and f in the kernel and T(e+f)=e
 
  • #3
So T(e)=e?

What does it mean in terms of projections?
 
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  • #4
Eh? What do you think a projection onto a subspace is? To me it *is* an idempotent linear map. Then nice thing about having an inner product (non-degenerat) around is that there is an obvious choice of complementary subspace
 
  • #5
What about the identity transformation? It's not an orthogonal projection of anything.
 
  • #6
Yes it is, onto the subspace itself.
 
  • #7
Just to be certain, is it equivalent to saying

[tex]T(v)=Proj_{im(T)}(v)[/tex] for all v? And not knowing what the image of T is a priori does not matter? And how does it follow that each vector in V is a combination of some vector in its image and its nullspace?
 
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  • #8
a projection is amap onto a subspace, that sends every vector to a vector in the subspace, and leaves vectorsd that are already in the subspace where they are.

so if V is a vector space and X is a subspace we want to project on, and if

Y is any complementary subspace, i.e. X and Y together generate V, and X and Y have only the zewro vector in common, then every vector in V can be written uniquely in the form x+y where x is in X and y is in Y.

Then the map f sending x+y to x, is a projection onto X, "along" Y.

Notice that f(f(v)) = v for all v, since once v gets into X it stays put. And also Y = ker(f), since vectors in Y go to zero.


Indeed any linear map f such that f^2 = f is asuch a projection.


f is called an "orthogonal" projection if Y = ker(f) is orthogonal to X = im(f).\

at least i think so, you should of course verify everything by proving all these either trivial or false statements.
 
  • #9
I figured it out. Of course I assumed that what is meant by "orthogonal projection onto its image" is that [tex]T(v)=Proj_{im(T)}(v)[/tex]. Thanks for the help.
 

1. What is an orthogonal projection?

An orthogonal projection is a method of representing a three-dimensional object on a two-dimensional surface in a way that preserves the relative sizes and shapes of the object's features. It involves projecting each point of the object onto a plane that is perpendicular to the viewing direction, resulting in a flattened representation of the object.

2. What is the purpose of using orthogonal projection?

Orthogonal projection is commonly used in engineering, architecture, and other fields to create accurate and realistic drawings of objects. It allows for precise measurements and calculations to be made on the projected image, making it a valuable tool for design and analysis.

3. How is orthogonal projection different from perspective projection?

While orthogonal projection preserves the relative sizes and shapes of the object's features, perspective projection takes into account the distortion that occurs when viewing objects from different angles. In perspective projection, objects that are farther away appear smaller, giving a more realistic representation of depth.

4. What are the types of orthogonal projection?

There are three main types of orthogonal projection: isometric, dimetric, and trimetric. Isometric projection uses equally spaced angles to project the object, while dimetric and trimetric projections use different angles for each axis. These types of projection are often used in different fields depending on the desired level of accuracy and realism.

5. What are the limitations of orthogonal projection?

One limitation of orthogonal projection is that it can only accurately represent objects that have parallel lines and right angles. Curved or angled surfaces may appear distorted in an orthogonal projection. Additionally, orthogonal projection does not account for perspective, so objects may appear distorted or unrealistic in terms of depth perception.

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