CLAIMS

1. A method of deriving Simplified depth coding (SDC) prediction values in three-dimensional video coding (3DVC), comprising calculating the SDC prediction values from neighboring reconstructed samples of a current block.

2. The method as claimed in claim 1, wherein the SDC prediction values are calculated as a function of the neighboring reconstructed samples of the current block, formulated as P = f ( j , x_{2} , · · · x_{n} ) ,where P is the prediction value and x_{\} , ¾, ... , x_{n} are neighboring reconstructed samples of the current block.

3. The method as claimed in claim 1, wherein intra-prediction samples for the current block are not generated in SDC.

4. The method as claimed in claim 1, wherein available neighboring reconstructed samples are filtered and unavailable neighboring reconstructed samples are replaced by the available ones, before they are used to calculate the SDC prediction values.

5. The method as claimed in claim 1 , wherein the calculated SDC prediction values are clipped to [MIN_VALUE, MAX_VALUE], where MIN_VALUE and

MAX_VALUE are the minimum and maximum sample values respectively.

6. The method as claimed in claim 2, wherein there can be one, two or more SDC prediction values, depending on the number of segments of the current block; and the SDC prediction values in different segments are calculated in different ways, formulated as P_{t} = f_{t} (x_{1}, x_{2},- - - x_{n} ) , where P_{t} is the SDC prediction value for the rth segment.

7. The method as claimed in claim 2, wherein the function is a linear function,

n

formulated as / ( x_{1} , x_{2} , · · · x_{n} ) = ^ a_{i}x_{i} , where <¾ is a real parameter.

i=l

8. The method as claimed in claim 2, wherein different functions are applied for different SDC modes, formulated as P_{m}= f_{m}{x_{l},x_{2},--- x_{n}) , where P_{m} is the prediction value for SDC mode m; and the SDC mode is signalled explicitly in a bit-stream or derived implicitly by a decoder.

9. The method as claimed in claim 2, wherein different functions are applied depending on which neighboring reconstructed samples are available.

10. The method as claimed in claim 2, wherein a neighboring reconstructed sample does not appear in the function if it is unavailable, formulated as f(x_{1},x_{2},---x_{n}) = f(x_{1},x_{2},...,x_{k}__{1},x_{k+1},---,x_{n}) , where ¾ is unavailable.

11. The method as claimed in claim 2, wherein function is a constant value, formulated as f(x_{1},x_{2},---x_{n}) = c, where c is a constant value.

12. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as P= (A+B+l)»l, where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples.

13. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as

(A+B+l)»l, If A and B are both available

P= A, If A is available only

B, If B is available only

MAX_VALUE/2, If A and B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples, and MAX_VALUE is a maximum sample value.

14. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as

(A+B+l)»l, If A and B are both available

P= A, If A is available only

B, If B is available only

128, If A and B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples, and MAX_VALUE is a maximum sample value.

15. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as

r (A+B+l)»l, If A and B are both available

P= I A, If A is available only

B, If B is available only

(MAX_VALUE+ MIN_VALUE +1)»1, If A and

B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples , and MAX_VALUE is a maximum sample value.

16. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as

(A+B)»l, If A and B are both available

A, If A is available only

B, If B is available only

MAX_VALUE/2, If A and B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples , and MAX_VALUE is a maximum sample value.

17. The method as claimed in claim 2, wherein the prediction value P for SDC mode DC is calculated as

(A+B)»l, If A and B are both available P= A, If A is available only

B, If B is available only

128, If A and B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples, and MAX_VALUE is a maximum sample value.

18. The method as claimed in claim 2 , wherein the prediction value P for SDC mode DC is calculated as

(A+B)»l, If A and B are both available

A, If A is available only

B, If B is available only

(MAX_VALUE+ MIN_VALUE )»1, If A and

B are neither available

where the neighboring reconstructed samples A and B are top left neighboring reconstructed samples, and MAX_VALUE is a maximum sample value.

19. The method as claimed in claim 2, wherein the prediction value P for SDC mode Planar is calculated as P= (X+Y+l) » 1, where the neighboring reconstructed samples X and Y are top left neighboring reconstructed samples.

20. The method as claimed in claim 2, wherein the prediction value P for SDC mode Planar is calculated as P= (X+Y) » 1, where the neighboring reconstructed samples X and Y are a bottom left neighboring reconstructed sample and a top right neighboring reconstructed sample respectively.

21. The method as claimed in claim 2, wherein there are two prediction values PO and PI for SDC mode DMM-1; and PO and PI are calculated as average values of neighboring reconstructed samples in segment 0 and segment 1 respectively.